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30 Sep 2014 17:43:36 +0000 Date: Tue, 30 Sep 2014 17:43:35 +0000 (UTC) From: "Harish Butani (JIRA)" To: hive-dev@hadoop.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Commented] (HIVE-8263) CBO : TPC-DS Q64 is item is joined last with store_sales while it should be first as it is the most selective MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: quoted-printable X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 [ https://issues.apache.org/jira/browse/HIVE-8263?page=3Dcom.atlassian.= jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=3D14153= 446#comment-14153446 ]=20 Harish Butani commented on HIVE-8263: ------------------------------------- Failure in 'groupby_bigdata' is not related to this patch. > CBO : TPC-DS Q64 is item is joined last with store_sales while it should = be first as it is the most selective > -------------------------------------------------------------------------= ------------------------------------ > > Key: HIVE-8263 > URL: https://issues.apache.org/jira/browse/HIVE-8263 > Project: Hive > Issue Type: Bug > Components: CBO > Affects Versions: 0.14.0 > Reporter: Mostafa Mokhtar > Assignee: Harish Butani > Fix For: 0.14.0 > > Attachments: HIVE-8263.1.patch, Q64_cbo_on_explain_log.txt.zip > > > Plan for TPC-DS Q64 shows that item is joined last with store_sales while= store_sales x item is the most selective join in the plan. > Interestingly predicate push down is applied on item but item comes so la= te in the join which most likely means that calculation of the join selecti= vity gave too high of a number of it was never considered. > This is a subset of the logical plan showing that item was joined very la= st > {code} > HiveProjectRel(_o__col0=3D[$0], _o__col1=3D[$2], _o__col2=3D[$3], _o__col= 3=3D[$4], _o__col4=3D[$5], _o__col5=3D[$6], _o__col6=3D[$7], _o__col7=3D[$8= ], _o__col8=3D[$9], _o__col9=3D[$10], _o__col10=3D[$11], _o__col11=3D[$12],= _o__col12=3D[$13], _o__col13=3D[$14], _o__col14=3D[$15], _o__col15=3D[$16]= , _o__col16=3D[$22], _o__col17=3D[$23], _o__col18=3D[$24], _o__col19=3D[$20= ], _o__col20=3D[$21]): rowcount =3D 1.0, cumulative cost =3D {1.15934037963= 22412E9 rows, 0.0 cpu, 0.0 io}, id =3D 990 > HiveFilterRel(condition=3D[<=3D($21, $13)]): rowcount =3D 1.0, cumula= tive cost =3D {1.1593403796322412E9 rows, 0.0 cpu, 0.0 io}, id =3D 988 > HiveProjectRel(_o__col0=3D[$0], _o__col1=3D[$1], _o__col2=3D[$2], _= o__col3=3D[$3], _o__col4=3D[$4], _o__col5=3D[$5], _o__col6=3D[$6], _o__col7= =3D[$7], _o__col8=3D[$8], _o__col9=3D[$9], _o__col10=3D[$10], _o__col11=3D[= $11], _o__col12=3D[$12], _o__col15=3D[$13], _o__col16=3D[$14], _o__col17=3D= [$15], _o__col18=3D[$16], _o__col13=3D[$17], _o__col20=3D[$18], _o__col30= =3D[$19], _o__col120=3D[$20], _o__col150=3D[$21], _o__col160=3D[$22], _o__c= ol170=3D[$23], _o__col180=3D[$24]): rowcount =3D 1.0, cumulative cost =3D {= 1.1593403796322412E9 rows, 0.0 cpu, 0.0 io}, id =3D 3571 > HiveJoinRel(condition=3D[AND(AND(=3D($1, $17), =3D($2, $18)), =3D= ($3, $19))], joinType=3D[inner]): rowcount =3D 1.0, cumulative cost =3D {1.= 1593403796322412E9 rows, 0.0 cpu, 0.0 io}, id =3D 3566 > HiveProjectRel(_o__col0=3D[$0], _o__col1=3D[$1], _o__col2=3D[$2= ], _o__col3=3D[$3], _o__col4=3D[$4], _o__col5=3D[$5], _o__col6=3D[$6], _o__= col7=3D[$7], _o__col8=3D[$8], _o__col9=3D[$9], _o__col10=3D[$10], _o__col11= =3D[$11], _o__col12=3D[$12], _o__col15=3D[$15], _o__col16=3D[$16], _o__col1= 7=3D[$17], _o__col18=3D[$18]): rowcount =3D 1.0, cumulative cost =3D {1.159= 3403776322412E9 rows, 0.0 cpu, 0.0 io}, id =3D 890 > HiveFilterRel(condition=3D[=3D($12, 2000)]): rowcount =3D 1.0= , cumulative cost =3D {1.1593403776322412E9 rows, 0.0 cpu, 0.0 io}, id =3D = 888 > HiveAggregateRel(group=3D[{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10= , 11, 12, 13, 14}], agg#0=3D[count()], agg#1=3D[sum($15)], agg#2=3D[sum($16= )], agg#3=3D[sum($17)]): rowcount =3D 1.0, cumulative cost =3D {1.159340377= 6322412E9 rows, 0.0 cpu, 0.0 io}, id =3D 886 > HiveProjectRel($f0=3D[$53], $f1=3D[$50], $f2=3D[$27], $f3= =3D[$28], $f4=3D[$39], $f5=3D[$40], $f6=3D[$41], $f7=3D[$42], $f8=3D[$44], = $f9=3D[$45], $f10=3D[$46], $f11=3D[$47], $f12=3D[$21], $f13=3D[$23], $f14= =3D[$25], $f15=3D[$9], $f16=3D[$10], $f17=3D[$11]): rowcount =3D 1.0, cumul= ative cost =3D {1.1593403776322412E9 rows, 0.0 cpu, 0.0 io}, id =3D 884 > HiveProjectRel(ss_sold_date_sk=3D[$17], ss_item_sk=3D[$= 18], ss_customer_sk=3D[$19], ss_cdemo_sk=3D[$20], ss_hdemo_sk=3D[$21], ss_a= ddr_sk=3D[$22], ss_store_sk=3D[$23], ss_promo_sk=3D[$24], ss_ticket_number= =3D[$25], ss_wholesale_cost=3D[$26], ss_list_price=3D[$27], ss_coupon_amt= =3D[$28], sr_item_sk=3D[$29], sr_ticket_number=3D[$30], c_customer_sk=3D[$3= 1], c_current_cdemo_sk=3D[$32], c_current_hdemo_sk=3D[$33], c_current_addr_= sk=3D[$34], c_first_shipto_date_sk=3D[$35], c_first_sales_date_sk=3D[$36], = d_date_sk=3D[$37], d_year=3D[$38], d_date_sk0=3D[$39], d_year0=3D[$40], d_d= ate_sk1=3D[$41], d_year1=3D[$42], s_store_sk=3D[$43], s_store_name=3D[$44],= s_zip=3D[$45], cd_demo_sk=3D[$46], cd_marital_status=3D[$47], cd_demo_sk0= =3D[$48], cd_marital_status0=3D[$49], p_promo_sk=3D[$0], hd_demo_sk=3D[$15]= , hd_income_band_sk=3D[$16], hd_demo_sk0=3D[$13], hd_income_band_sk0=3D[$14= ], ca_address_sk=3D[$6], ca_street_number=3D[$7], ca_street_name=3D[$8], ca= _city=3D[$9], ca_zip=3D[$10], ca_address_sk0=3D[$1], ca_street_number0=3D[$= 2], ca_street_name0=3D[$3], ca_city0=3D[$4], ca_zip0=3D[$5], ib_income_band= _sk=3D[$12], ib_income_band_sk0=3D[$11], i_item_sk=3D[$51], i_current_price= =3D[$52], i_color=3D[$53], i_product_name=3D[$54], _o__col0=3D[$50]): rowco= unt =3D 1.0, cumulative cost =3D {1.1593403776322412E9 rows, 0.0 cpu, 0.0 i= o}, id =3D 3564 > HiveJoinRel(condition=3D[=3D($24, $0)], joinType=3D[i= nner]): rowcount =3D 1.0, cumulative cost =3D {1.1593403776322412E9 rows, 0= .0 cpu, 0.0 io}, id =3D 3562 > HiveProjectRel(p_promo_sk=3D[$0]): rowcount =3D 450= .0, cumulative cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 928 > HiveTableScanRel(table=3D[[tpcds_bin_partitioned_= orc_200.promotion]]): rowcount =3D 450.0, cumulative cost =3D {0}, id =3D 5= 8 > HiveJoinRel(condition=3D[=3D($33, $0)], joinType=3D= [inner]): rowcount =3D 1.0, cumulative cost =3D {1.1593399266322412E9 rows,= 0.0 cpu, 0.0 io}, id =3D 3560 > HiveProjectRel(ca_address_sk=3D[$0], ca_street_nu= mber=3D[$2], ca_street_name=3D[$3], ca_city=3D[$6], ca_zip=3D[$9]): rowcoun= t =3D 800000.0, cumulative cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 940 > HiveTableScanRel(table=3D[[tpcds_bin_partitione= d_orc_200.customer_address]]): rowcount =3D 800000.0, cumulative cost =3D {= 0}, id =3D 61 > HiveJoinRel(condition=3D[=3D($16, $0)], joinType= =3D[inner]): rowcount =3D 1.0, cumulative cost =3D {1.1585399256322412E9 ro= ws, 0.0 cpu, 0.0 io}, id =3D 3558 > HiveProjectRel(ca_address_sk=3D[$0], ca_street_= number=3D[$2], ca_street_name=3D[$3], ca_city=3D[$6], ca_zip=3D[$9]): rowco= unt =3D 800000.0, cumulative cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 9= 40 > HiveTableScanRel(table=3D[[tpcds_bin_partitio= ned_orc_200.customer_address]]): rowcount =3D 800000.0, cumulative cost =3D= {0}, id =3D 61 > HiveJoinRel(condition=3D[=3D($3, $0)], joinType= =3D[inner]): rowcount =3D 1.0, cumulative cost =3D {1.1577399246322412E9 ro= ws, 0.0 cpu, 0.0 io}, id =3D 3556 > HiveProjectRel(ib_income_band_sk=3D[$0]): row= count =3D 20.0, cumulative cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 948 > HiveTableScanRel(table=3D[[tpcds_bin_partit= ioned_orc_200.income_band]]): rowcount =3D 20.0, cumulative cost =3D {0}, i= d =3D 63 > HiveJoinRel(condition=3D[=3D($4, $0)], joinTy= pe=3D[inner]): rowcount =3D 1.0, cumulative cost =3D {1.1577399036322412E9 = rows, 0.0 cpu, 0.0 io}, id =3D 3554 > HiveProjectRel(ib_income_band_sk=3D[$0]): r= owcount =3D 20.0, cumulative cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 9= 48 > HiveTableScanRel(table=3D[[tpcds_bin_part= itioned_orc_200.income_band]]): rowcount =3D 20.0, cumulative cost =3D {0},= id =3D 63 > HiveJoinRel(condition=3D[=3D($5, $38)], joi= nType=3D[inner]): rowcount =3D 1.0, cumulative cost =3D {1.1577398826322412= E9 rows, 0.0 cpu, 0.0 io}, id =3D 3552 > HiveJoinRel(condition=3D[=3D($20, $0)], j= oinType=3D[inner]): rowcount =3D 1.0, cumulative cost =3D {1.15773988063224= 12E9 rows, 0.0 cpu, 0.0 io}, id =3D 3550 > HiveProjectRel(hd_demo_sk=3D[$0], hd_in= come_band_sk=3D[$1]): rowcount =3D 7200.0, cumulative cost =3D {0.0 rows, 0= .0 cpu, 0.0 io}, id =3D 932 > HiveTableScanRel(table=3D[[tpcds_bin_= partitioned_orc_200.household_demographics]]): rowcount =3D 7200.0, cumulat= ive cost =3D {0}, id =3D 53 > HiveJoinRel(condition=3D[=3D($6, $0)], = joinType=3D[inner]): rowcount =3D 1.0, cumulative cost =3D {1.1577326796322= 412E9 rows, 0.0 cpu, 0.0 io}, id =3D 3548 > HiveProjectRel(hd_demo_sk=3D[$0], hd_= income_band_sk=3D[$1]): rowcount =3D 7200.0, cumulative cost =3D {0.0 rows,= 0.0 cpu, 0.0 io}, id =3D 932 > HiveTableScanRel(table=3D[[tpcds_bi= n_partitioned_orc_200.household_demographics]]): rowcount =3D 7200.0, cumul= ative cost =3D {0}, id =3D 53 > HiveJoinRel(condition=3D[=3D($1, $33)= ], joinType=3D[inner]): rowcount =3D 1.0, cumulative cost =3D {1.1577254786= 322412E9 rows, 0.0 cpu, 0.0 io}, id =3D 2795 > HiveFilterRel(condition=3D[<>($30, = $32)]): rowcount =3D 1.0, cumulative cost =3D {1.1577254766322412E9 rows, 0= .0 cpu, 0.0 io}, id =3D 832 > HiveProjectRel(ss_sold_date_sk=3D= [$0], ss_item_sk=3D[$1], ss_customer_sk=3D[$2], ss_cdemo_sk=3D[$3], ss_hdem= o_sk=3D[$4], ss_addr_sk=3D[$5], ss_store_sk=3D[$6], ss_promo_sk=3D[$7], ss_= ticket_number=3D[$8], ss_wholesale_cost=3D[$9], ss_list_price=3D[$10], ss_c= oupon_amt=3D[$11], sr_item_sk=3D[$31], sr_ticket_number=3D[$32], c_customer= _sk=3D[$21], c_current_cdemo_sk=3D[$22], c_current_hdemo_sk=3D[$23], c_curr= ent_addr_sk=3D[$24], c_first_shipto_date_sk=3D[$25], c_first_sales_date_sk= =3D[$26], d_date_sk=3D[$14], d_year=3D[$15], d_date_sk0=3D[$27], d_year0=3D= [$28], d_date_sk1=3D[$29], d_year1=3D[$30], s_store_sk=3D[$16], s_store_nam= e=3D[$17], s_zip=3D[$18], cd_demo_sk=3D[$12], cd_marital_status=3D[$13], cd= _demo_sk0=3D[$19], cd_marital_status0=3D[$20]): rowcount =3D 3.957996536045= 2816, cumulative cost =3D {1.1577254766322412E9 rows, 0.0 cpu, 0.0 io}, id = =3D 1998 > HiveJoinRel(condition=3D[AND(= =3D($1, $31), =3D($8, $32))], joinType=3D[inner]): rowcount =3D 3.957996536= 0452816, cumulative cost =3D {1.1577254766322412E9 rows, 0.0 cpu, 0.0 io}, = id =3D 1996 > HiveJoinRel(condition=3D[=3D(= $2, $21)], joinType=3D[inner]): rowcount =3D 1.0, cumulative cost =3D {1.10= 21474706322412E9 rows, 0.0 cpu, 0.0 io}, id =3D 1994 > HiveJoinRel(condition=3D[= =3D($6, $16)], joinType=3D[inner]): rowcount =3D 1.0, cumulative cost =3D {= 1.1021474686322412E9 rows, 0.0 cpu, 0.0 io}, id =3D 1987 > HiveJoinRel(condition=3D[= =3D($0, $14)], joinType=3D[inner]): rowcount =3D 299.6322411714753, cumulat= ive cost =3D {1.102146957E9 rows, 0.0 cpu, 0.0 io}, id =3D 1985 > HiveJoinRel(condition= =3D[=3D($3, $12)], joinType=3D[inner]): rowcount =3D 5.50076554E8, cumulati= ve cost =3D {5.51997354E8 rows, 0.0 cpu, 0.0 io}, id =3D 1569 > HiveProjectRel(ss_sol= d_date_sk=3D[$0], ss_item_sk=3D[$2], ss_customer_sk=3D[$3], ss_cdemo_sk=3D[= $4], ss_hdemo_sk=3D[$5], ss_addr_sk=3D[$6], ss_store_sk=3D[$7], ss_promo_sk= =3D[$8], ss_ticket_number=3D[$9], ss_wholesale_cost=3D[$11], ss_list_price= =3D[$12], ss_coupon_amt=3D[$19]): rowcount =3D 5.50076554E8, cumulative cos= t =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 892 > HiveTableScanRel(ta= ble=3D[[tpcds_bin_partitioned_orc_200.store_sales]]): rowcount =3D 5.500765= 54E8, cumulative cost =3D {0}, id =3D 55 > HiveProjectRel(cd_dem= o_sk=3D[$0], cd_marital_status=3D[$2]): rowcount =3D 1920800.0, cumulative = cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 918 > HiveTableScanRel(ta= ble=3D[[tpcds_bin_partitioned_orc_200.customer_demographics]]): rowcount = =3D 1920800.0, cumulative cost =3D {0}, id =3D 56 > HiveProjectRel(d_date_s= k=3D[$0], d_year=3D[$6]): rowcount =3D 73049.0, cumulative cost =3D {0.0 ro= ws, 0.0 cpu, 0.0 io}, id =3D 902 > HiveTableScanRel(tabl= e=3D[[tpcds_bin_partitioned_orc_200.date_dim]]): rowcount =3D 73049.0, cumu= lative cost =3D {0}, id =3D 65 > HiveProjectRel(s_store_sk= =3D[$0], s_store_name=3D[$5], s_zip=3D[$25]): rowcount =3D 212.0, cumulativ= e cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 914 > HiveTableScanRel(table= =3D[[tpcds_bin_partitioned_orc_200.store]]): rowcount =3D 212.0, cumulative= cost =3D {0}, id =3D 54 > HiveJoinRel(condition=3D[= =3D($6, $10)], joinType=3D[inner]): rowcount =3D 1.0, cumulative cost =3D {= 5266899.0 rows, 0.0 cpu, 0.0 io}, id =3D 1992 > HiveJoinRel(condition=3D[= =3D($7, $8)], joinType=3D[inner]): rowcount =3D 1.0, cumulative cost =3D {5= 193849.0 rows, 0.0 cpu, 0.0 io}, id =3D 1990 > HiveJoinRel(condition= =3D[=3D($3, $0)], joinType=3D[inner]): rowcount =3D 1600000.0, cumulative c= ost =3D {3520800.0 rows, 0.0 cpu, 0.0 io}, id =3D 1578 > HiveProjectRel(cd_dem= o_sk=3D[$0], cd_marital_status=3D[$2]): rowcount =3D 1920800.0, cumulative = cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 918 > HiveTableScanRel(ta= ble=3D[[tpcds_bin_partitioned_orc_200.customer_demographics]]): rowcount = =3D 1920800.0, cumulative cost =3D {0}, id =3D 56 > HiveProjectRel(c_cust= omer_sk=3D[$0], c_current_cdemo_sk=3D[$2], c_current_hdemo_sk=3D[$3], c_cur= rent_addr_sk=3D[$4], c_first_shipto_date_sk=3D[$5], c_first_sales_date_sk= =3D[$6]): rowcount =3D 1600000.0, cumulative cost =3D {0.0 rows, 0.0 cpu, 0= .0 io}, id =3D 898 > HiveTableScanRel(ta= ble=3D[[tpcds_bin_partitioned_orc_200.customer]]): rowcount =3D 1600000.0, = cumulative cost =3D {0}, id =3D 59 > HiveProjectRel(d_date_s= k=3D[$0], d_year=3D[$6]): rowcount =3D 73049.0, cumulative cost =3D {0.0 ro= ws, 0.0 cpu, 0.0 io}, id =3D 902 > HiveTableScanRel(tabl= e=3D[[tpcds_bin_partitioned_orc_200.date_dim]]): rowcount =3D 73049.0, cumu= lative cost =3D {0}, id =3D 65 > HiveProjectRel(d_date_sk= =3D[$0], d_year=3D[$6]): rowcount =3D 73049.0, cumulative cost =3D {0.0 row= s, 0.0 cpu, 0.0 io}, id =3D 902 > HiveTableScanRel(table= =3D[[tpcds_bin_partitioned_orc_200.date_dim]]): rowcount =3D 73049.0, cumul= ative cost =3D {0}, id =3D 65 > HiveProjectRel(sr_item_sk=3D[= $2], sr_ticket_number=3D[$9]): rowcount =3D 5.5578005E7, cumulative cost = =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 894 > HiveTableScanRel(table=3D[[= tpcds_bin_partitioned_orc_200.store_returns]]): rowcount =3D 5.5578005E7, c= umulative cost =3D {0}, id =3D 62 > HiveProjectRel(_o__col0=3D[$0]): ro= wcount =3D 1.0, cumulative cost =3D {3.15348608E8 rows, 0.0 cpu, 0.0 io}, i= d =3D 880 > HiveFilterRel(condition=3D[>($1, = *(CAST(2):DOUBLE NOT NULL, $2))]): rowcount =3D 1.0, cumulative cost =3D {3= .15348608E8 rows, 0.0 cpu, 0.0 io}, id =3D 878 > HiveAggregateRel(group=3D[{0}],= agg#0=3D[sum($1)], agg#1=3D[sum($2)]): rowcount =3D 38846.0, cumulative co= st =3D {3.15348608E8 rows, 0.0 cpu, 0.0 io}, id =3D 876 > HiveProjectRel($f0=3D[$0], $f= 1=3D[$2], $f2=3D[+(+($5, $6), $7)]): rowcount =3D 6.692553251460564E8, cumu= lative cost =3D {3.15348608E8 rows, 0.0 cpu, 0.0 io}, id =3D 874 > HiveProjectRel(cs_item_sk= =3D[$0], cs_order_number=3D[$1], cs_ext_list_price=3D[$2], cr_item_sk=3D[$3= ], cr_order_number=3D[$4], cr_refunded_cash=3D[$5], cr_reversed_charge=3D[$= 6], cr_store_credit=3D[$7]): rowcount =3D 6.692553251460564E8, cumulative c= ost =3D {3.15348608E8 rows, 0.0 cpu, 0.0 io}, id =3D 1132 > HiveJoinRel(condition=3D[= AND(=3D($0, $3), =3D($1, $4))], joinType=3D[inner]): rowcount =3D 6.6925532= 51460564E8, cumulative cost =3D {3.15348608E8 rows, 0.0 cpu, 0.0 io}, id = =3D 1127 > HiveProjectRel(cs_item_= sk=3D[$15], cs_order_number=3D[$17], cs_ext_list_price=3D[$25]): rowcount = =3D 2.86549727E8, cumulative cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 9= 62 > HiveTableScanRel(tabl= e=3D[[tpcds_bin_partitioned_orc_200.catalog_sales]]): rowcount =3D 2.865497= 27E8, cumulative cost =3D {0}, id =3D 45 > HiveProjectRel(cr_item_= sk=3D[$2], cr_order_number=3D[$16], cr_refunded_cash=3D[$23], cr_reversed_c= harge=3D[$24], cr_store_credit=3D[$25]): rowcount =3D 2.8798881E7, cumulati= ve cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 964 > HiveTableScanRel(tabl= e=3D[[tpcds_bin_partitioned_orc_200.catalog_returns]]): rowcount =3D 2.8798= 881E7, cumulative cost =3D {0}, id =3D 46 > HiveFilterRel(condition=3D[AND(in($2, 'ma= roon', 'burnished', 'dim', 'steel', 'navajo', 'chocolate'), between(false, = $1, 35, +(35, 10)), between(false, $1, +(35, 1), +(35, 15)))]): rowcount = =3D 1.0, cumulative cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 864 > HiveProjectRel(i_item_sk=3D[$0], i_curr= ent_price=3D[$5], i_color=3D[$17], i_product_name=3D[$21]): rowcount =3D 48= 000.0, cumulative cost =3D {0.0 rows, 0.0 cpu, 0.0 io}, id =3D 862 > HiveTableScanRel(table=3D[[tpcds_bin_= partitioned_orc_200.item]]): rowcount =3D 48000.0, cumulative cost =3D {0},= id =3D 68 > {code} > Physical plan=20 > {code} > STAGE PLANS: > Stage: Stage-1 > Tez > Edges: > Map 10 <- Map 40 (BROADCAST_EDGE) > Map 16 <- Map 2 (BROADCAST_EDGE), Map 23 (BROADCAST_EDGE), Map 6 = (BROADCAST_EDGE) > Map 19 <- Map 42 (BROADCAST_EDGE) > Map 33 <- Map 35 (BROADCAST_EDGE) > Map 35 <- Map 1 (BROADCAST_EDGE), Map 16 (BROADCAST_EDGE), Map 3 = (BROADCAST_EDGE), Map 8 (BROADCAST_EDGE) > Map 36 <- Map 18 (BROADCAST_EDGE), Map 25 (BROADCAST_EDGE), Map 4= 1 (BROADCAST_EDGE) > Map 38 <- Map 15 (BROADCAST_EDGE), Map 31 (BROADCAST_EDGE), Map 3= 6 (BROADCAST_EDGE), Map 5 (BROADCAST_EDGE) > Map 4 <- Map 38 (BROADCAST_EDGE) > Reducer 11 <- Map 10 (SIMPLE_EDGE), Map 22 (BROADCAST_EDGE), Map = 24 (BROADCAST_EDGE), Map 26 (BROADCAST_EDGE), Map 27 (BROADCAST_EDGE), Map = 30 (BROADCAST_EDGE), Map 32 (BROADCAST_EDGE), Map 39 (BROADCAST_EDGE), Map = 4 (BROADCAST_EDGE), Map 7 (BROADCAST_EDGE) > Reducer 12 <- Reducer 11 (SIMPLE_EDGE) > Reducer 13 <- Reducer 12 (SIMPLE_EDGE), Reducer 21 (SIMPLE_EDGE) > Reducer 14 <- Reducer 13 (SIMPLE_EDGE) > Reducer 20 <- Map 17 (BROADCAST_EDGE), Map 19 (SIMPLE_EDGE), Map = 28 (BROADCAST_EDGE), Map 29 (BROADCAST_EDGE), Map 33 (BROADCAST_EDGE), Map = 34 (BROADCAST_EDGE), Map 37 (BROADCAST_EDGE), Map 43 (BROADCAST_EDGE), Map = 44 (BROADCAST_EDGE), Map 9 (BROADCAST_EDGE) > Reducer 21 <- Reducer 20 (SIMPLE_EDGE) > DagName: mmokhtar_20140925174747_6fa8c67a-6d24-43cc-8fbb-3be14937b8= b1:1 > Vertices: > Map 1=20 > Map Operator Tree: > TableScan > alias: d1 > filterExpr: d_date_sk is not null (type: boolean) > Statistics: Num rows: 73049 Data size: 81741831 Basic s= tats: COMPLETE Column stats: NONE > Filter Operator > predicate: d_date_sk is not null (type: boolean) > Statistics: Num rows: 36525 Data size: 40871475 Basic= stats: COMPLETE Column stats: NONE > Select Operator > expressions: d_date_sk (type: int), d_year (type: i= nt) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 36525 Data size: 40871475 Bas= ic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 36525 Data size: 40871475 B= asic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: int) > Execution mode: vectorized > Map 10=20 > Map Operator Tree: > TableScan > alias: catalog_sales > filterExpr: (cs_item_sk is not null and cs_order_number= is not null) (type: boolean) > Statistics: Num rows: 286549727 Data size: 38890158232 = Basic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (cs_item_sk is not null and cs_order_numbe= r is not null) (type: boolean) > Statistics: Num rows: 71637432 Data size: 9722539591 = Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: cs_item_sk (type: int), cs_order_numbe= r (type: int), cs_ext_list_price (type: float) > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 71637432 Data size: 972253959= 1 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col0} {_col2} > 1 {_col2} {_col3} {_col4} > keys: > 0 _col0 (type: int), _col1 (type: int) > 1 _col0 (type: int), _col1 (type: int) > outputColumnNames: _col0, _col2, _col5, _col6, _c= ol7 > input vertices: > 1 Map 40 > Statistics: Num rows: 78801176 Data size: 1069479= 4240 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col0 (type: int), _col2 (type: fl= oat), ((_col5 + _col6) + _col7) (type: float) > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 78801176 Data size: 10694= 794240 Basic stats: COMPLETE Column stats: NONE > Group By Operator > aggregations: sum(_col1), sum(_col2) > keys: _col0 (type: int) > mode: hash > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 78801176 Data size: 106= 94794240 Basic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: = int) > Statistics: Num rows: 78801176 Data size: 1= 0694794240 Basic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: double), _c= ol2 (type: double) > Execution mode: vectorized > Map 15=20 > Map Operator Tree: > TableScan > alias: customer > filterExpr: (((((c_current_cdemo_sk is not null and c_f= irst_sales_date_sk is not null) and c_first_shipto_date_sk is not null) and= c_customer_sk is not null) and c_current_hdemo_sk is not null) and c_curre= nt_addr_sk is not null) (type: boolean) > Statistics: Num rows: 1600000 Data size: 1376033128 Bas= ic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (((((c_current_cdemo_sk is not null and c_= first_sales_date_sk is not null) and c_first_shipto_date_sk is not null) an= d c_customer_sk is not null) and c_current_hdemo_sk is not null) and c_curr= ent_addr_sk is not null) (type: boolean) > Statistics: Num rows: 25000 Data size: 21500517 Basic= stats: COMPLETE Column stats: NONE > Select Operator > expressions: c_customer_sk (type: int), c_current_c= demo_sk (type: int), c_current_hdemo_sk (type: int), c_current_addr_sk (typ= e: int), c_first_shipto_date_sk (type: int), c_first_sales_date_sk (type: i= nt) > outputColumnNames: _col0, _col1, _col2, _col3, _col= 4, _col5 > Statistics: Num rows: 25000 Data size: 21500517 Bas= ic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col1 (type: int) > sort order: + > Map-reduce partition columns: _col1 (type: int) > Statistics: Num rows: 25000 Data size: 21500517 B= asic stats: COMPLETE Column stats: NONE > value expressions: _col0 (type: int), _col2 (type= : int), _col3 (type: int), _col4 (type: int), _col5 (type: int) > Execution mode: vectorized > Map 16=20 > Map Operator Tree: > TableScan > alias: cd1 > filterExpr: cd_demo_sk is not null (type: boolean) > Statistics: Num rows: 1920800 Data size: 718379200 Basi= c stats: COMPLETE Column stats: NONE > Filter Operator > predicate: cd_demo_sk is not null (type: boolean) > Statistics: Num rows: 960400 Data size: 359189600 Bas= ic stats: COMPLETE Column stats: NONE > Select Operator > expressions: cd_demo_sk (type: int), cd_marital_sta= tus (type: string) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 960400 Data size: 359189600 B= asic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col0} {_col1} {_col2} {_col4} {_col5} {_col= 6} {_col7} {_col8} {_col9} {_col10} {_col11} > 1 {_col1} > keys: > 0 _col3 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col0, _col1, _col2, _col4, _c= ol5, _col6, _col7, _col8, _col9, _col10, _col11, _col13 > input vertices: > 0 Map 6 > Statistics: Num rows: 1181805 Data size: 51579732= Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col4} {_col5} {_col6} {_c= ol7} {_col8} {_col9} {_col10} {_col11} {_col13} > 1=20 > keys: > 0 _col0 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col2, _col4, _col5, = _col6, _col7, _col8, _col9, _col10, _col11, _col13 > input vertices: > 1 Map 23 > Statistics: Num rows: 1299985 Data size: 567377= 08 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col4} {_col5} {_col7} {= _col8} {_col9} {_col10} {_col11} {_col13} > 1 {_col1} {_col2} > keys: > 0 _col6 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col2, _col4, _col5= , _col7, _col8, _col9, _col10, _col11, _col13, _col17, _col18 > input vertices: > 1 Map 2 > Statistics: Num rows: 1429983 Data size: 6241= 1480 Basic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col2 (type: int) > sort order: + > Map-reduce partition columns: _col2 (type: = int) > Statistics: Num rows: 1429983 Data size: 62= 411480 Basic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: int), _col4= (type: int), _col5 (type: int), _col7 (type: int), _col8 (type: int), _col= 9 (type: float), _col10 (type: float), _col11 (type: float), _col13 (type: = string), _col17 (type: string), _col18 (type: string) > Execution mode: vectorized > Map 17=20 > Map Operator Tree: > TableScan > alias: ib1 > filterExpr: ib_income_band_sk is not null (type: boolea= n) > Statistics: Num rows: 20 Data size: 240 Basic stats: CO= MPLETE Column stats: NONE > Filter Operator > predicate: ib_income_band_sk is not null (type: boole= an) > Statistics: Num rows: 10 Data size: 120 Basic stats: = COMPLETE Column stats: NONE > Select Operator > expressions: ib_income_band_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 10 Data size: 120 Basic stats= : COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 10 Data size: 120 Basic sta= ts: COMPLETE Column stats: NONE > Execution mode: vectorized > Map 18=20 > Map Operator Tree: > TableScan > alias: store_sales > filterExpr: ((((((((ss_cdemo_sk is not null and ss_sold= _date_sk is not null) and ss_store_sk is not null) and ss_customer_sk is no= t null) and ss_item_sk is not null) and ss_ticket_number is not null) and s= s_hdemo_sk is not null) and ss_addr_sk is not null) and ss_promo_sk is not = null) (type: boolean) > Statistics: Num rows: 550076554 Data size: 24008004411 = Basic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: ((((((((ss_cdemo_sk is not null and ss_sol= d_date_sk is not null) and ss_store_sk is not null) and ss_customer_sk is n= ot null) and ss_item_sk is not null) and ss_ticket_number is not null) and = ss_hdemo_sk is not null) and ss_addr_sk is not null) and ss_promo_sk is not= null) (type: boolean) > Statistics: Num rows: 1074369 Data size: 46890665 Bas= ic stats: COMPLETE Column stats: NONE > Select Operator > expressions: ss_sold_date_sk (type: int), ss_item_s= k (type: int), ss_customer_sk (type: int), ss_cdemo_sk (type: int), ss_hdem= o_sk (type: int), ss_addr_sk (type: int), ss_store_sk (type: int), ss_promo= _sk (type: int), ss_ticket_number (type: int), ss_wholesale_cost (type: flo= at), ss_list_price (type: float), ss_coupon_amt (type: float) > outputColumnNames: _col0, _col1, _col2, _col3, _col= 4, _col5, _col6, _col7, _col8, _col9, _col10, _col11 > Statistics: Num rows: 1074369 Data size: 46890665 B= asic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col3 (type: int) > sort order: + > Map-reduce partition columns: _col3 (type: int) > Statistics: Num rows: 1074369 Data size: 46890665= Basic stats: COMPLETE Column stats: NONE > value expressions: _col0 (type: int), _col1 (type= : int), _col2 (type: int), _col4 (type: int), _col5 (type: int), _col6 (typ= e: int), _col7 (type: int), _col8 (type: int), _col9 (type: float), _col10 = (type: float), _col11 (type: float) > Execution mode: vectorized > Map 19=20 > Map Operator Tree: > TableScan > alias: catalog_sales > filterExpr: (cs_item_sk is not null and cs_order_number= is not null) (type: boolean) > Statistics: Num rows: 286549727 Data size: 38890158232 = Basic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (cs_item_sk is not null and cs_order_numbe= r is not null) (type: boolean) > Statistics: Num rows: 71637432 Data size: 9722539591 = Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: cs_item_sk (type: int), cs_order_numbe= r (type: int), cs_ext_list_price (type: float) > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 71637432 Data size: 972253959= 1 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col0} {_col2} > 1 {_col2} {_col3} {_col4} > keys: > 0 _col0 (type: int), _col1 (type: int) > 1 _col0 (type: int), _col1 (type: int) > outputColumnNames: _col0, _col2, _col5, _col6, _c= ol7 > input vertices: > 1 Map 42 > Statistics: Num rows: 78801176 Data size: 1069479= 4240 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col0 (type: int), _col2 (type: fl= oat), ((_col5 + _col6) + _col7) (type: float) > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 78801176 Data size: 10694= 794240 Basic stats: COMPLETE Column stats: NONE > Group By Operator > aggregations: sum(_col1), sum(_col2) > keys: _col0 (type: int) > mode: hash > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 78801176 Data size: 106= 94794240 Basic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: = int) > Statistics: Num rows: 78801176 Data size: 1= 0694794240 Basic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: double), _c= ol2 (type: double) > Execution mode: vectorized > Map 2=20 > Map Operator Tree: > TableScan > alias: store > filterExpr: ((s_store_sk is not null and s_store_name i= s not null) and s_zip is not null) (type: boolean) > Statistics: Num rows: 212 Data size: 405680 Basic stats= : COMPLETE Column stats: NONE > Filter Operator > predicate: ((s_store_sk is not null and s_store_name = is not null) and s_zip is not null) (type: boolean) > Statistics: Num rows: 27 Data size: 51666 Basic stats= : COMPLETE Column stats: NONE > Select Operator > expressions: s_store_sk (type: int), s_store_name (= type: string), s_zip (type: string) > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 27 Data size: 51666 Basic sta= ts: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 27 Data size: 51666 Basic s= tats: COMPLETE Column stats: NONE > value expressions: _col1 (type: string), _col2 (t= ype: string) > Execution mode: vectorized > Map 22=20 > Map Operator Tree: > TableScan > alias: ib1 > filterExpr: ib_income_band_sk is not null (type: boolea= n) > Statistics: Num rows: 20 Data size: 240 Basic stats: CO= MPLETE Column stats: NONE > Filter Operator > predicate: ib_income_band_sk is not null (type: boole= an) > Statistics: Num rows: 10 Data size: 120 Basic stats: = COMPLETE Column stats: NONE > Select Operator > expressions: ib_income_band_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 10 Data size: 120 Basic stats= : COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 10 Data size: 120 Basic sta= ts: COMPLETE Column stats: NONE > Execution mode: vectorized > Map 23=20 > Map Operator Tree: > TableScan > alias: d1 > filterExpr: (d_date_sk is not null and (d_year =3D 2000= )) (type: boolean) > Statistics: Num rows: 73049 Data size: 81741831 Basic s= tats: COMPLETE Column stats: NONE > Filter Operator > predicate: (d_date_sk is not null and (d_year =3D 200= 0)) (type: boolean) > Statistics: Num rows: 18262 Data size: 20435178 Basic= stats: COMPLETE Column stats: NONE > Select Operator > expressions: d_date_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 18262 Data size: 20435178 Bas= ic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 18262 Data size: 20435178 B= asic stats: COMPLETE Column stats: NONE > Execution mode: vectorized > Map 24=20 > Map Operator Tree: > TableScan > alias: hd1 > filterExpr: (hd_demo_sk is not null and hd_income_band_= sk is not null) (type: boolean) > Statistics: Num rows: 7200 Data size: 799 Basic stats: = COMPLETE Column stats: NONE > Filter Operator > predicate: (hd_demo_sk is not null and hd_income_band= _sk is not null) (type: boolean) > Statistics: Num rows: 1800 Data size: 199 Basic stats= : COMPLETE Column stats: NONE > Select Operator > expressions: hd_demo_sk (type: int), hd_income_band= _sk (type: int) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 1800 Data size: 199 Basic sta= ts: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 1800 Data size: 199 Basic s= tats: COMPLETE Column stats: NONE > value expressions: _col1 (type: int) > Execution mode: vectorized > Map 25=20 > Map Operator Tree: > TableScan > alias: d1 > filterExpr: (d_date_sk is not null and (d_year =3D 2001= )) (type: boolean) > Statistics: Num rows: 73049 Data size: 81741831 Basic s= tats: COMPLETE Column stats: NONE > Filter Operator > predicate: (d_date_sk is not null and (d_year =3D 200= 1)) (type: boolean) > Statistics: Num rows: 18262 Data size: 20435178 Basic= stats: COMPLETE Column stats: NONE > Select Operator > expressions: d_date_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 18262 Data size: 20435178 Bas= ic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 18262 Data size: 20435178 B= asic stats: COMPLETE Column stats: NONE > Execution mode: vectorized > Map 26=20 > Map Operator Tree: > TableScan > alias: promotion > filterExpr: p_promo_sk is not null (type: boolean) > Statistics: Num rows: 450 Data size: 530848 Basic stats= : COMPLETE Column stats: NONE > Filter Operator > predicate: p_promo_sk is not null (type: boolean) > Statistics: Num rows: 225 Data size: 265424 Basic sta= ts: COMPLETE Column stats: NONE > Select Operator > expressions: p_promo_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 225 Data size: 265424 Basic s= tats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 225 Data size: 265424 Basic= stats: COMPLETE Column stats: NONE > Execution mode: vectorized > Map 27=20 > Map Operator Tree: > TableScan > alias: hd1 > filterExpr: (hd_demo_sk is not null and hd_income_band_= sk is not null) (type: boolean) > Statistics: Num rows: 7200 Data size: 799 Basic stats: = COMPLETE Column stats: NONE > Filter Operator > predicate: (hd_demo_sk is not null and hd_income_band= _sk is not null) (type: boolean) > Statistics: Num rows: 1800 Data size: 199 Basic stats= : COMPLETE Column stats: NONE > Select Operator > expressions: hd_demo_sk (type: int), hd_income_band= _sk (type: int) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 1800 Data size: 199 Basic sta= ts: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 1800 Data size: 199 Basic s= tats: COMPLETE Column stats: NONE > value expressions: _col1 (type: int) > Execution mode: vectorized > Map 28=20 > Map Operator Tree: > TableScan > alias: ad1 > filterExpr: ca_address_sk is not null (type: boolean) > Statistics: Num rows: 800000 Data size: 811903688 Basic= stats: COMPLETE Column stats: NONE > Filter Operator > predicate: ca_address_sk is not null (type: boolean) > Statistics: Num rows: 400000 Data size: 405951844 Bas= ic stats: COMPLETE Column stats: NONE > Select Operator > expressions: ca_address_sk (type: int), ca_street_n= umber (type: string), ca_street_name (type: string), ca_city (type: string)= , ca_zip (type: string) > outputColumnNames: _col0, _col1, _col2, _col3, _col= 4 > Statistics: Num rows: 400000 Data size: 405951844 B= asic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 400000 Data size: 405951844= Basic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: string), _col2 (t= ype: string), _col3 (type: string), _col4 (type: string) > Execution mode: vectorized > Map 29=20 > Map Operator Tree: > TableScan > alias: item > filterExpr: ((((i_color) IN ('maroon', 'burnished', 'di= m', 'steel', 'navajo', 'chocolate') and i_current_price BETWEEN 35 AND 45) = and i_current_price BETWEEN 36 AND 50) and i_item_sk is not null) (type: bo= olean) > Statistics: Num rows: 48000 Data size: 68732712 Basic s= tats: COMPLETE Column stats: NONE > Filter Operator > predicate: ((((i_color) IN ('maroon', 'burnished', 'd= im', 'steel', 'navajo', 'chocolate') and i_current_price BETWEEN 35 AND 45)= and i_current_price BETWEEN 36 AND 50) and i_item_sk is not null) (type: b= oolean) > Statistics: Num rows: 3000 Data size: 4295794 Basic s= tats: COMPLETE Column stats: NONE > Select Operator > expressions: i_item_sk (type: int), i_product_name = (type: string) > outputColumnNames: _col0, _col3 > Statistics: Num rows: 3000 Data size: 4295794 Basic= stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 3000 Data size: 4295794 Bas= ic stats: COMPLETE Column stats: NONE > value expressions: _col3 (type: string) > Execution mode: vectorized > Map 3=20 > Map Operator Tree: > TableScan > alias: customer > filterExpr: (((((c_current_cdemo_sk is not null and c_f= irst_sales_date_sk is not null) and c_first_shipto_date_sk is not null) and= c_customer_sk is not null) and c_current_hdemo_sk is not null) and c_curre= nt_addr_sk is not null) (type: boolean) > Statistics: Num rows: 1600000 Data size: 1376033128 Bas= ic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (((((c_current_cdemo_sk is not null and c_= first_sales_date_sk is not null) and c_first_shipto_date_sk is not null) an= d c_customer_sk is not null) and c_current_hdemo_sk is not null) and c_curr= ent_addr_sk is not null) (type: boolean) > Statistics: Num rows: 25000 Data size: 21500517 Basic= stats: COMPLETE Column stats: NONE > Select Operator > expressions: c_customer_sk (type: int), c_current_c= demo_sk (type: int), c_current_hdemo_sk (type: int), c_current_addr_sk (typ= e: int), c_first_shipto_date_sk (type: int), c_first_sales_date_sk (type: i= nt) > outputColumnNames: _col0, _col1, _col2, _col3, _col= 4, _col5 > Statistics: Num rows: 25000 Data size: 21500517 Bas= ic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col1 (type: int) > sort order: + > Map-reduce partition columns: _col1 (type: int) > Statistics: Num rows: 25000 Data size: 21500517 B= asic stats: COMPLETE Column stats: NONE > value expressions: _col0 (type: int), _col2 (type= : int), _col3 (type: int), _col4 (type: int), _col5 (type: int) > Execution mode: vectorized > Map 30=20 > Map Operator Tree: > TableScan > alias: ib1 > filterExpr: ib_income_band_sk is not null (type: boolea= n) > Statistics: Num rows: 20 Data size: 240 Basic stats: CO= MPLETE Column stats: NONE > Filter Operator > predicate: ib_income_band_sk is not null (type: boole= an) > Statistics: Num rows: 10 Data size: 120 Basic stats: = COMPLETE Column stats: NONE > Select Operator > expressions: ib_income_band_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 10 Data size: 120 Basic stats= : COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 10 Data size: 120 Basic sta= ts: COMPLETE Column stats: NONE > Execution mode: vectorized > Map 31=20 > Map Operator Tree: > TableScan > alias: d1 > filterExpr: d_date_sk is not null (type: boolean) > Statistics: Num rows: 73049 Data size: 81741831 Basic s= tats: COMPLETE Column stats: NONE > Filter Operator > predicate: d_date_sk is not null (type: boolean) > Statistics: Num rows: 36525 Data size: 40871475 Basic= stats: COMPLETE Column stats: NONE > Select Operator > expressions: d_date_sk (type: int), d_year (type: i= nt) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 36525 Data size: 40871475 Bas= ic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 36525 Data size: 40871475 B= asic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: int) > Execution mode: vectorized > Map 32=20 > Map Operator Tree: > TableScan > alias: ad1 > filterExpr: ca_address_sk is not null (type: boolean) > Statistics: Num rows: 800000 Data size: 811903688 Basic= stats: COMPLETE Column stats: NONE > Filter Operator > predicate: ca_address_sk is not null (type: boolean) > Statistics: Num rows: 400000 Data size: 405951844 Bas= ic stats: COMPLETE Column stats: NONE > Select Operator > expressions: ca_address_sk (type: int), ca_street_n= umber (type: string), ca_street_name (type: string), ca_city (type: string)= , ca_zip (type: string) > outputColumnNames: _col0, _col1, _col2, _col3, _col= 4 > Statistics: Num rows: 400000 Data size: 405951844 B= asic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 400000 Data size: 405951844= Basic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: string), _col2 (t= ype: string), _col3 (type: string), _col4 (type: string) > Execution mode: vectorized > Map 33=20 > Map Operator Tree: > TableScan > alias: store_returns > filterExpr: (sr_item_sk is not null and sr_ticket_numbe= r is not null) (type: boolean) > Statistics: Num rows: 55578005 Data size: 4377627636 Ba= sic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (sr_item_sk is not null and sr_ticket_numb= er is not null) (type: boolean) > Statistics: Num rows: 13894502 Data size: 1094406968 = Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: sr_item_sk (type: int), sr_ticket_numb= er (type: int) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 13894502 Data size: 109440696= 8 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col4} {_col5} {_col7} {_col9} {_col= 10} {_col11} {_col13} {_col17} {_col18} {_col20} {_col23} {_col24} {_col28}= {_col30} > 1=20 > keys: > 0 _col1 (type: int), _col8 (type: int) > 1 _col0 (type: int), _col1 (type: int) > outputColumnNames: _col1, _col4, _col5, _col7, _c= ol9, _col10, _col11, _col13, _col17, _col18, _col20, _col23, _col24, _col28= , _col30 > input vertices: > 0 Map 35 > Statistics: Num rows: 15283953 Data size: 1203847= 680 Basic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (_col13 <> _col20) (type: boolean) > Statistics: Num rows: 15283953 Data size: 12038= 47680 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: int), _col10 (type:= float), _col11 (type: float), _col23 (type: int), _col24 (type: int), 2000= (type: int), _col28 (type: int), _col30 (type: int), _col17 (type: string)= , _col18 (type: string), _col4 (type: int), _col5 (type: int), _col7 (type:= int), _col9 (type: float) > outputColumnNames: _col1, _col10, _col11, _co= l16, _col17, _col21, _col23, _col25, _col27, _col28, _col4, _col5, _col7, _= col9 > Statistics: Num rows: 15283953 Data size: 120= 3847680 Basic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col1 (type: int) > sort order: + > Map-reduce partition columns: _col1 (type: = int) > Statistics: Num rows: 15283953 Data size: 1= 203847680 Basic stats: COMPLETE Column stats: NONE > value expressions: _col4 (type: int), _col5= (type: int), _col7 (type: int), _col9 (type: float), _col10 (type: float),= _col11 (type: float), _col16 (type: int), _col17 (type: int), _col21 (type= : int), _col23 (type: int), _col25 (type: int), _col27 (type: string), _col= 28 (type: string) > Execution mode: vectorized > Map 34=20 > Map Operator Tree: > TableScan > alias: promotion > filterExpr: p_promo_sk is not null (type: boolean) > Statistics: Num rows: 450 Data size: 530848 Basic stats= : COMPLETE Column stats: NONE > Filter Operator > predicate: p_promo_sk is not null (type: boolean) > Statistics: Num rows: 225 Data size: 265424 Basic sta= ts: COMPLETE Column stats: NONE > Select Operator > expressions: p_promo_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 225 Data size: 265424 Basic s= tats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 225 Data size: 265424 Basic= stats: COMPLETE Column stats: NONE > Execution mode: vectorized > Map 35=20 > Map Operator Tree: > TableScan > alias: cd1 > filterExpr: cd_demo_sk is not null (type: boolean) > Statistics: Num rows: 1920800 Data size: 718379200 Basi= c stats: COMPLETE Column stats: NONE > Filter Operator > predicate: cd_demo_sk is not null (type: boolean) > Statistics: Num rows: 960400 Data size: 359189600 Bas= ic stats: COMPLETE Column stats: NONE > Select Operator > expressions: cd_demo_sk (type: int), cd_marital_sta= tus (type: string) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 960400 Data size: 359189600 B= asic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} > 1 {_col0} {_col2} {_col3} {_col4} {_col5} > keys: > 0 _col0 (type: int) > 1 _col1 (type: int) > outputColumnNames: _col1, _col2, _col4, _col5, _c= ol6, _col7 > input vertices: > 1 Map 3 > Statistics: Num rows: 1056440 Data size: 39510857= 6 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col4} {_col5} {_col6} > 1 {_col1} > keys: > 0 _col7 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col2, _col4, _col5, = _col6, _col9 > input vertices: > 1 Map 8 > Statistics: Num rows: 1162084 Data size: 434619= 456 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col4} {_col5} {_col9} > 1 {_col1} > keys: > 0 _col6 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col2, _col4, _col5= , _col9, _col11 > input vertices: > 1 Map 1 > Statistics: Num rows: 1278292 Data size: 4780= 81408 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: string), _col11 (= type: int), _col2 (type: int), _col4 (type: int), _col5 (type: int), _col9 = (type: int) > outputColumnNames: _col1, _col11, _col2, _c= ol4, _col5, _col9 > Statistics: Num rows: 1278292 Data size: 47= 8081408 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col4} {_col5} {_col7} {_col= 8} {_col9} {_col10} {_col11} {_col13} {_col17} {_col18} > 1 {_col1} {_col4} {_col5} {_col9} {_col= 11} > keys: > 0 _col2 (type: int) > 1 _col2 (type: int) > outputColumnNames: _col1, _col4, _col5, _= col7, _col8, _col9, _col10, _col11, _col13, _col17, _col18, _col20, _col23,= _col24, _col28, _col30 > input vertices: > 0 Map 16 > Statistics: Num rows: 1572981 Data size: = 68652632 Basic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col1 (type: int), _co= l8 (type: int) > sort order: ++ > Map-reduce partition columns: _col1 (ty= pe: int), _col8 (type: int) > Statistics: Num rows: 1572981 Data size= : 68652632 Basic stats: COMPLETE Column stats: NONE > value expressions: _col4 (type: int), _= col5 (type: int), _col7 (type: int), _col9 (type: float), _col10 (type: flo= at), _col11 (type: float), _col13 (type: string), _col17 (type: string), _c= ol18 (type: string), _col20 (type: string), _col23 (type: int), _col24 (typ= e: int), _col28 (type: int), _col30 (type: int) > Execution mode: vectorized > Map 36=20 > Map Operator Tree: > TableScan > alias: cd1 > filterExpr: cd_demo_sk is not null (type: boolean) > Statistics: Num rows: 1920800 Data size: 718379200 Basi= c stats: COMPLETE Column stats: NONE > Filter Operator > predicate: cd_demo_sk is not null (type: boolean) > Statistics: Num rows: 960400 Data size: 359189600 Bas= ic stats: COMPLETE Column stats: NONE > Select Operator > expressions: cd_demo_sk (type: int), cd_marital_sta= tus (type: string) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 960400 Data size: 359189600 B= asic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col0} {_col1} {_col2} {_col4} {_col5} {_col= 6} {_col7} {_col8} {_col9} {_col10} {_col11} > 1 {_col1} > keys: > 0 _col3 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col0, _col1, _col2, _col4, _c= ol5, _col6, _col7, _col8, _col9, _col10, _col11, _col13 > input vertices: > 0 Map 18 > Statistics: Num rows: 1181805 Data size: 51579732= Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col4} {_col5} {_col6} {_c= ol7} {_col8} {_col9} {_col10} {_col11} {_col13} > 1=20 > keys: > 0 _col0 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col2, _col4, _col5, = _col6, _col7, _col8, _col9, _col10, _col11, _col13 > input vertices: > 1 Map 25 > Statistics: Num rows: 1299985 Data size: 567377= 08 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col4} {_col5} {_col7} {= _col8} {_col9} {_col10} {_col11} {_col13} > 1 {_col1} {_col2} > keys: > 0 _col6 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col2, _col4, _col5= , _col7, _col8, _col9, _col10, _col11, _col13, _col17, _col18 > input vertices: > 1 Map 41 > Statistics: Num rows: 1429983 Data size: 6241= 1480 Basic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col2 (type: int) > sort order: + > Map-reduce partition columns: _col2 (type: = int) > Statistics: Num rows: 1429983 Data size: 62= 411480 Basic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: int), _col4= (type: int), _col5 (type: int), _col7 (type: int), _col8 (type: int), _col= 9 (type: float), _col10 (type: float), _col11 (type: float), _col13 (type: = string), _col17 (type: string), _col18 (type: string) > Execution mode: vectorized > Map 37=20 > Map Operator Tree: > TableScan > alias: ib1 > filterExpr: ib_income_band_sk is not null (type: boolea= n) > Statistics: Num rows: 20 Data size: 240 Basic stats: CO= MPLETE Column stats: NONE > Filter Operator > predicate: ib_income_band_sk is not null (type: boole= an) > Statistics: Num rows: 10 Data size: 120 Basic stats: = COMPLETE Column stats: NONE > Select Operator > expressions: ib_income_band_sk (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 10 Data size: 120 Basic stats= : COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 10 Data size: 120 Basic sta= ts: COMPLETE Column stats: NONE > Execution mode: vectorized > Map 38=20 > Map Operator Tree: > TableScan > alias: cd1 > filterExpr: cd_demo_sk is not null (type: boolean) > Statistics: Num rows: 1920800 Data size: 718379200 Basi= c stats: COMPLETE Column stats: NONE > Filter Operator > predicate: cd_demo_sk is not null (type: boolean) > Statistics: Num rows: 960400 Data size: 359189600 Bas= ic stats: COMPLETE Column stats: NONE > Select Operator > expressions: cd_demo_sk (type: int), cd_marital_sta= tus (type: string) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 960400 Data size: 359189600 B= asic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} > 1 {_col0} {_col2} {_col3} {_col4} {_col5} > keys: > 0 _col0 (type: int) > 1 _col1 (type: int) > outputColumnNames: _col1, _col2, _col4, _col5, _c= ol6, _col7 > input vertices: > 1 Map 15 > Statistics: Num rows: 1056440 Data size: 39510857= 6 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col4} {_col5} {_col6} > 1 {_col1} > keys: > 0 _col7 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col2, _col4, _col5, = _col6, _col9 > input vertices: > 1 Map 31 > Statistics: Num rows: 1162084 Data size: 434619= 456 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col4} {_col5} {_col9} > 1 {_col1} > keys: > 0 _col6 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col2, _col4, _col5= , _col9, _col11 > input vertices: > 1 Map 5 > Statistics: Num rows: 1278292 Data size: 4780= 81408 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: string), _col11 (= type: int), _col2 (type: int), _col4 (type: int), _col5 (type: int), _col9 = (type: int) > outputColumnNames: _col1, _col11, _col2, _c= ol4, _col5, _col9 > Statistics: Num rows: 1278292 Data size: 47= 8081408 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col4} {_col5} {_col7} {_col= 8} {_col9} {_col10} {_col11} {_col13} {_col17} {_col18} > 1 {_col1} {_col4} {_col5} {_col9} {_col= 11} > keys: > 0 _col2 (type: int) > 1 _col2 (type: int) > outputColumnNames: _col1, _col4, _col5, _= col7, _col8, _col9, _col10, _col11, _col13, _col17, _col18, _col20, _col23,= _col24, _col28, _col30 > input vertices: > 0 Map 36 > Statistics: Num rows: 1572981 Data size: = 68652632 Basic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col1 (type: int), _co= l8 (type: int) > sort order: ++ > Map-reduce partition columns: _col1 (ty= pe: int), _col8 (type: int) > Statistics: Num rows: 1572981 Data size= : 68652632 Basic stats: COMPLETE Column stats: NONE > value expressions: _col4 (type: int), _= col5 (type: int), _col7 (type: int), _col9 (type: float), _col10 (type: flo= at), _col11 (type: float), _col13 (type: string), _col17 (type: string), _c= ol18 (type: string), _col20 (type: string), _col23 (type: int), _col24 (typ= e: int), _col28 (type: int), _col30 (type: int) > Execution mode: vectorized > Map 39=20 > Map Operator Tree: > TableScan > alias: item > filterExpr: ((((i_color) IN ('maroon', 'burnished', 'di= m', 'steel', 'navajo', 'chocolate') and i_current_price BETWEEN 35 AND 45) = and i_current_price BETWEEN 36 AND 50) and i_item_sk is not null) (type: bo= olean) > Statistics: Num rows: 48000 Data size: 68732712 Basic s= tats: COMPLETE Column stats: NONE > Filter Operator > predicate: ((((i_color) IN ('maroon', 'burnished', 'd= im', 'steel', 'navajo', 'chocolate') and i_current_price BETWEEN 35 AND 45)= and i_current_price BETWEEN 36 AND 50) and i_item_sk is not null) (type: b= oolean) > Statistics: Num rows: 3000 Data size: 4295794 Basic s= tats: COMPLETE Column stats: NONE > Select Operator > expressions: i_item_sk (type: int), i_product_name = (type: string) > outputColumnNames: _col0, _col3 > Statistics: Num rows: 3000 Data size: 4295794 Basic= stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 3000 Data size: 4295794 Bas= ic stats: COMPLETE Column stats: NONE > value expressions: _col3 (type: string) > Execution mode: vectorized > Map 4=20 > Map Operator Tree: > TableScan > alias: store_returns > filterExpr: (sr_item_sk is not null and sr_ticket_numbe= r is not null) (type: boolean) > Statistics: Num rows: 55578005 Data size: 4377627636 Ba= sic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (sr_item_sk is not null and sr_ticket_numb= er is not null) (type: boolean) > Statistics: Num rows: 13894502 Data size: 1094406968 = Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: sr_item_sk (type: int), sr_ticket_numb= er (type: int) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 13894502 Data size: 109440696= 8 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col4} {_col5} {_col7} {_col9} {_col= 10} {_col11} {_col13} {_col17} {_col18} {_col20} {_col23} {_col24} {_col28}= {_col30} > 1=20 > keys: > 0 _col1 (type: int), _col8 (type: int) > 1 _col0 (type: int), _col1 (type: int) > outputColumnNames: _col1, _col4, _col5, _col7, _c= ol9, _col10, _col11, _col13, _col17, _col18, _col20, _col23, _col24, _col28= , _col30 > input vertices: > 0 Map 38 > Statistics: Num rows: 15283953 Data size: 1203847= 680 Basic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (_col13 <> _col20) (type: boolean) > Statistics: Num rows: 15283953 Data size: 12038= 47680 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: int), _col10 (type:= float), _col11 (type: float), _col23 (type: int), _col24 (type: int), 2001= (type: int), _col28 (type: int), _col30 (type: int), _col17 (type: string)= , _col18 (type: string), _col4 (type: int), _col5 (type: int), _col7 (type:= int), _col9 (type: float) > outputColumnNames: _col1, _col10, _col11, _co= l16, _col17, _col21, _col23, _col25, _col27, _col28, _col4, _col5, _col7, _= col9 > Statistics: Num rows: 15283953 Data size: 120= 3847680 Basic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col1 (type: int) > sort order: + > Map-reduce partition columns: _col1 (type: = int) > Statistics: Num rows: 15283953 Data size: 1= 203847680 Basic stats: COMPLETE Column stats: NONE > value expressions: _col4 (type: int), _col5= (type: int), _col7 (type: int), _col9 (type: float), _col10 (type: float),= _col11 (type: float), _col16 (type: int), _col17 (type: int), _col21 (type= : int), _col23 (type: int), _col25 (type: int), _col27 (type: string), _col= 28 (type: string) > Execution mode: vectorized > Map 40=20 > Map Operator Tree: > TableScan > alias: catalog_returns > filterExpr: (cr_item_sk is not null and cr_order_number= is not null) (type: boolean) > Statistics: Num rows: 28798881 Data size: 3057234680 Ba= sic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (cr_item_sk is not null and cr_order_numbe= r is not null) (type: boolean) > Statistics: Num rows: 7199721 Data size: 764308749 Ba= sic stats: COMPLETE Column stats: NONE > Select Operator > expressions: cr_item_sk (type: int), cr_order_numbe= r (type: int), cr_refunded_cash (type: float), cr_reversed_charge (type: fl= oat), cr_store_credit (type: float) > outputColumnNames: _col0, _col1, _col2, _col3, _col= 4 > Statistics: Num rows: 7199721 Data size: 764308749 = Basic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int), _col1 (type: = int) > sort order: ++ > Map-reduce partition columns: _col0 (type: int), = _col1 (type: int) > Statistics: Num rows: 7199721 Data size: 76430874= 9 Basic stats: COMPLETE Column stats: NONE > value expressions: _col2 (type: float), _col3 (ty= pe: float), _col4 (type: float) > Execution mode: vectorized > Map 41=20 > Map Operator Tree: > TableScan > alias: store > filterExpr: ((s_store_sk is not null and s_store_name i= s not null) and s_zip is not null) (type: boolean) > Statistics: Num rows: 212 Data size: 405680 Basic stats= : COMPLETE Column stats: NONE > Filter Operator > predicate: ((s_store_sk is not null and s_store_name = is not null) and s_zip is not null) (type: boolean) > Statistics: Num rows: 27 Data size: 51666 Basic stats= : COMPLETE Column stats: NONE > Select Operator > expressions: s_store_sk (type: int), s_store_name (= type: string), s_zip (type: string) > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 27 Data size: 51666 Basic sta= ts: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 27 Data size: 51666 Basic s= tats: COMPLETE Column stats: NONE > value expressions: _col1 (type: string), _col2 (t= ype: string) > Execution mode: vectorized > Map 42=20 > Map Operator Tree: > TableScan > alias: catalog_returns > filterExpr: (cr_item_sk is not null and cr_order_number= is not null) (type: boolean) > Statistics: Num rows: 28798881 Data size: 3057234680 Ba= sic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (cr_item_sk is not null and cr_order_numbe= r is not null) (type: boolean) > Statistics: Num rows: 7199721 Data size: 764308749 Ba= sic stats: COMPLETE Column stats: NONE > Select Operator > expressions: cr_item_sk (type: int), cr_order_numbe= r (type: int), cr_refunded_cash (type: float), cr_reversed_charge (type: fl= oat), cr_store_credit (type: float) > outputColumnNames: _col0, _col1, _col2, _col3, _col= 4 > Statistics: Num rows: 7199721 Data size: 764308749 = Basic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int), _col1 (type: = int) > sort order: ++ > Map-reduce partition columns: _col0 (type: int), = _col1 (type: int) > Statistics: Num rows: 7199721 Data size: 76430874= 9 Basic stats: COMPLETE Column stats: NONE > value expressions: _col2 (type: float), _col3 (ty= pe: float), _col4 (type: float) > Execution mode: vectorized > Map 43=20 > Map Operator Tree: > TableScan > alias: ad1 > filterExpr: ca_address_sk is not null (type: boolean) > Statistics: Num rows: 800000 Data size: 811903688 Basic= stats: COMPLETE Column stats: NONE > Filter Operator > predicate: ca_address_sk is not null (type: boolean) > Statistics: Num rows: 400000 Data size: 405951844 Bas= ic stats: COMPLETE Column stats: NONE > Select Operator > expressions: ca_address_sk (type: int), ca_street_n= umber (type: string), ca_street_name (type: string), ca_city (type: string)= , ca_zip (type: string) > outputColumnNames: _col0, _col1, _col2, _col3, _col= 4 > Statistics: Num rows: 400000 Data size: 405951844 B= asic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 400000 Data size: 405951844= Basic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: string), _col2 (t= ype: string), _col3 (type: string), _col4 (type: string) > Execution mode: vectorized > Map 44=20 > Map Operator Tree: > TableScan > alias: hd1 > filterExpr: (hd_demo_sk is not null and hd_income_band_= sk is not null) (type: boolean) > Statistics: Num rows: 7200 Data size: 799 Basic stats: = COMPLETE Column stats: NONE > Filter Operator > predicate: (hd_demo_sk is not null and hd_income_band= _sk is not null) (type: boolean) > Statistics: Num rows: 1800 Data size: 199 Basic stats= : COMPLETE Column stats: NONE > Select Operator > expressions: hd_demo_sk (type: int), hd_income_band= _sk (type: int) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 1800 Data size: 199 Basic sta= ts: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 1800 Data size: 199 Basic s= tats: COMPLETE Column stats: NONE > value expressions: _col1 (type: int) > Execution mode: vectorized > Map 5=20 > Map Operator Tree: > TableScan > alias: d1 > filterExpr: d_date_sk is not null (type: boolean) > Statistics: Num rows: 73049 Data size: 81741831 Basic s= tats: COMPLETE Column stats: NONE > Filter Operator > predicate: d_date_sk is not null (type: boolean) > Statistics: Num rows: 36525 Data size: 40871475 Basic= stats: COMPLETE Column stats: NONE > Select Operator > expressions: d_date_sk (type: int), d_year (type: i= nt) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 36525 Data size: 40871475 Bas= ic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 36525 Data size: 40871475 B= asic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: int) > Execution mode: vectorized > Map 6=20 > Map Operator Tree: > TableScan > alias: store_sales > filterExpr: ((((((((ss_cdemo_sk is not null and ss_sold= _date_sk is not null) and ss_store_sk is not null) and ss_customer_sk is no= t null) and ss_item_sk is not null) and ss_ticket_number is not null) and s= s_hdemo_sk is not null) and ss_addr_sk is not null) and ss_promo_sk is not = null) (type: boolean) > Statistics: Num rows: 550076554 Data size: 24008004411 = Basic stats: COMPLETE Column stats: NONE > Filter Operator > predicate: ((((((((ss_cdemo_sk is not null and ss_sol= d_date_sk is not null) and ss_store_sk is not null) and ss_customer_sk is n= ot null) and ss_item_sk is not null) and ss_ticket_number is not null) and = ss_hdemo_sk is not null) and ss_addr_sk is not null) and ss_promo_sk is not= null) (type: boolean) > Statistics: Num rows: 1074369 Data size: 46890665 Bas= ic stats: COMPLETE Column stats: NONE > Select Operator > expressions: ss_sold_date_sk (type: int), ss_item_s= k (type: int), ss_customer_sk (type: int), ss_cdemo_sk (type: int), ss_hdem= o_sk (type: int), ss_addr_sk (type: int), ss_store_sk (type: int), ss_promo= _sk (type: int), ss_ticket_number (type: int), ss_wholesale_cost (type: flo= at), ss_list_price (type: float), ss_coupon_amt (type: float) > outputColumnNames: _col0, _col1, _col2, _col3, _col= 4, _col5, _col6, _col7, _col8, _col9, _col10, _col11 > Statistics: Num rows: 1074369 Data size: 46890665 B= asic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col3 (type: int) > sort order: + > Map-reduce partition columns: _col3 (type: int) > Statistics: Num rows: 1074369 Data size: 46890665= Basic stats: COMPLETE Column stats: NONE > value expressions: _col0 (type: int), _col1 (type= : int), _col2 (type: int), _col4 (type: int), _col5 (type: int), _col6 (typ= e: int), _col7 (type: int), _col8 (type: int), _col9 (type: float), _col10 = (type: float), _col11 (type: float) > Execution mode: vectorized > Map 7=20 > Map Operator Tree: > TableScan > alias: ad1 > filterExpr: ca_address_sk is not null (type: boolean) > Statistics: Num rows: 800000 Data size: 811903688 Basic= stats: COMPLETE Column stats: NONE > Filter Operator > predicate: ca_address_sk is not null (type: boolean) > Statistics: Num rows: 400000 Data size: 405951844 Bas= ic stats: COMPLETE Column stats: NONE > Select Operator > expressions: ca_address_sk (type: int), ca_street_n= umber (type: string), ca_street_name (type: string), ca_city (type: string)= , ca_zip (type: string) > outputColumnNames: _col0, _col1, _col2, _col3, _col= 4 > Statistics: Num rows: 400000 Data size: 405951844 B= asic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 400000 Data size: 405951844= Basic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: string), _col2 (t= ype: string), _col3 (type: string), _col4 (type: string) > Execution mode: vectorized > Map 8=20 > Map Operator Tree: > TableScan > alias: d1 > filterExpr: d_date_sk is not null (type: boolean) > Statistics: Num rows: 73049 Data size: 81741831 Basic s= tats: COMPLETE Column stats: NONE > Filter Operator > predicate: d_date_sk is not null (type: boolean) > Statistics: Num rows: 36525 Data size: 40871475 Basic= stats: COMPLETE Column stats: NONE > Select Operator > expressions: d_date_sk (type: int), d_year (type: i= nt) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 36525 Data size: 40871475 Bas= ic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 36525 Data size: 40871475 B= asic stats: COMPLETE Column stats: NONE > value expressions: _col1 (type: int) > Execution mode: vectorized > Map 9=20 > Map Operator Tree: > TableScan > alias: hd1 > filterExpr: (hd_demo_sk is not null and hd_income_band_= sk is not null) (type: boolean) > Statistics: Num rows: 7200 Data size: 799 Basic stats: = COMPLETE Column stats: NONE > Filter Operator > predicate: (hd_demo_sk is not null and hd_income_band= _sk is not null) (type: boolean) > Statistics: Num rows: 1800 Data size: 199 Basic stats= : COMPLETE Column stats: NONE > Select Operator > expressions: hd_demo_sk (type: int), hd_income_band= _sk (type: int) > outputColumnNames: _col0, _col1 > Statistics: Num rows: 1800 Data size: 199 Basic sta= ts: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int) > sort order: + > Map-reduce partition columns: _col0 (type: int) > Statistics: Num rows: 1800 Data size: 199 Basic s= tats: COMPLETE Column stats: NONE > value expressions: _col1 (type: int) > Execution mode: vectorized > Reducer 11=20 > Reduce Operator Tree: > Group By Operator > aggregations: sum(VALUE._col0), sum(VALUE._col1) > keys: KEY._col0 (type: int) > mode: mergepartial > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 39400588 Data size: 5347397120 Basi= c stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (_col1 > (UDFToDouble(2) * _col2)) (type: bo= olean) > Statistics: Num rows: 13133529 Data size: 1782465661 Ba= sic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col0 (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 13133529 Data size: 1782465661 = Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col4} {_col5} {_col7} {_col9} {_col10= } {_col11} {_col16} {_col17} {_col21} {_col23} {_col25} {_col27} {_col28} > 1=20 > keys: > 0 _col1 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col4, _col5, _col7, _col= 9, _col10, _col11, _col16, _col17, _col21, _col23, _col25, _col27, _col28 > input vertices: > 0 Map 4 > Statistics: Num rows: 16812348 Data size: 132423244= 8 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: int), _col10 (type: flo= at), _col11 (type: float), _col16 (type: int), _col17 (type: int), _col21 (= type: int), _col23 (type: int), _col25 (type: int), _col27 (type: string), = _col28 (type: string), _col4 (type: int), _col5 (type: int), _col7 (type: i= nt), _col9 (type: float) > outputColumnNames: _col1, _col10, _col11, _col16,= _col17, _col21, _col23, _col25, _col27, _col28, _col4, _col5, _col7, _col9 > Statistics: Num rows: 16812348 Data size: 1324232= 448 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} > 1 {_col1} {_col5} {_col7} {_col9} {_col10} {_= col11} {_col16} {_col17} {_col21} {_col23} {_col25} {_col27} {_col28} > keys: > 0 _col0 (type: int) > 1 _col4 (type: int) > outputColumnNames: _col1, _col3, _col7, _col9, = _col11, _col12, _col13, _col18, _col19, _col23, _col25, _col27, _col29, _co= l30 > input vertices: > 0 Map 24 > Statistics: Num rows: 18493584 Data size: 14566= 55744 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: int), _col11 (type:= float), _col12 (type: float), _col13 (type: float), _col18 (type: int), _c= ol19 (type: int), _col23 (type: int), _col25 (type: int), _col27 (type: int= ), _col29 (type: string), _col3 (type: int), _col30 (type: string), _col7 (= type: int), _col9 (type: int) > outputColumnNames: _col1, _col11, _col12, _co= l13, _col18, _col19, _col23, _col25, _col27, _col29, _col3, _col30, _col7, = _col9 > Statistics: Num rows: 18493584 Data size: 145= 6655744 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} > 1 {_col1} {_col3} {_col7} {_col9} {_col11= } {_col12} {_col13} {_col19} {_col23} {_col25} {_col27} {_col29} {_col30} > keys: > 0 _col0 (type: int) > 1 _col18 (type: int) > outputColumnNames: _col1, _col3, _col5, _co= l9, _col11, _col13, _col14, _col15, _col21, _col25, _col27, _col29, _col31,= _col32 > input vertices: > 0 Map 27 > Statistics: Num rows: 20342942 Data size: 1= 602321408 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col3} {_col9} {_col11} {_co= l13} {_col14} {_col15} {_col21} {_col25} {_col27} {_col29} {_col31} {_col32= } > 1 {_col0} {_col3} > keys: > 0 _col5 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col3, _col9, _= col11, _col13, _col14, _col15, _col21, _col25, _col27, _col29, _col31, _col= 32, _col38, _col41 > input vertices: > 1 Map 39 > Statistics: Num rows: 22377236 Data size:= 1762553600 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: int), _col11 = (type: int), _col13 (type: float), _col14 (type: float), _col15 (type: floa= t), _col21 (type: int), _col25 (type: int), _col27 (type: int), _col29 (typ= e: int), _col3 (type: int), _col31 (type: string), _col32 (type: string), _= col38 (type: int), _col41 (type: string), _col9 (type: int) > outputColumnNames: _col1, _col11, _col1= 3, _col14, _col15, _col21, _col25, _col27, _col29, _col3, _col31, _col32, _= col38, _col41, _col9 > Statistics: Num rows: 22377236 Data siz= e: 1762553600 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0=20 > 1 {_col1} {_col9} {_col11} {_col13}= {_col14} {_col15} {_col21} {_col25} {_col27} {_col29} {_col31} {_col32} {_= col38} {_col41} > keys: > 0 _col0 (type: int) > 1 _col3 (type: int) > outputColumnNames: _col2, _col10, _co= l12, _col14, _col15, _col16, _col22, _col26, _col28, _col30, _col32, _col33= , _col39, _col42 > input vertices: > 0 Map 22 > Statistics: Num rows: 24614960 Data s= ize: 1938808960 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col10 (type: int), _c= ol12 (type: int), _col14 (type: float), _col15 (type: float), _col16 (type:= float), _col2 (type: int), _col22 (type: int), _col26 (type: int), _col28 = (type: int), _col30 (type: int), _col32 (type: string), _col33 (type: strin= g), _col39 (type: int), _col42 (type: string) > outputColumnNames: _col10, _col12, = _col14, _col15, _col16, _col2, _col22, _col26, _col28, _col30, _col32, _col= 33, _col39, _col42 > Statistics: Num rows: 24614960 Data= size: 1938808960 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0=20 > 1 {_col10} {_col12} {_col14} {_= col15} {_col16} {_col22} {_col26} {_col28} {_col30} {_col32} {_col33} {_col= 39} {_col42} > keys: > 0 _col0 (type: int) > 1 _col2 (type: int) > outputColumnNames: _col11, _col13= , _col15, _col16, _col17, _col23, _col27, _col29, _col31, _col33, _col34, _= col40, _col43 > input vertices: > 0 Map 30 > Statistics: Num rows: 27076456 Da= ta size: 2132689920 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col11 (type: int)= , _col13 (type: int), _col15 (type: float), _col16 (type: float), _col17 (t= ype: float), _col23 (type: int), _col27 (type: int), _col29 (type: int), _c= ol31 (type: int), _col33 (type: string), _col34 (type: string), _col40 (typ= e: int), _col43 (type: string) > outputColumnNames: _col11, _col= 13, _col15, _col16, _col17, _col23, _col27, _col29, _col31, _col33, _col34,= _col40, _col43 > Statistics: Num rows: 27076456 = Data size: 2132689920 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col3} {= _col4} > 1 {_col13} {_col15} {_col16= } {_col17} {_col23} {_col27} {_col29} {_col31} {_col33} {_col34} {_col40} {= _col43} > keys: > 0 _col0 (type: int) > 1 _col11 (type: int) > outputColumnNames: _col1, _co= l2, _col3, _col4, _col18, _col20, _col21, _col22, _col28, _col32, _col34, _= col36, _col38, _col39, _col45, _col48 > input vertices: > 0 Map 32 > Statistics: Num rows: 2978410= 2 Data size: 2345958912 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: s= tring), _col18 (type: int), _col2 (type: string), _col20 (type: float), _co= l21 (type: float), _col22 (type: float), _col28 (type: int), _col3 (type: s= tring), _col32 (type: int), _col34 (type: int), _col36 (type: int), _col38 = (type: string), _col39 (type: string), _col4 (type: string), _col45 (type: = int), _col48 (type: string) > outputColumnNames: _col1, _= col18, _col2, _col20, _col21, _col22, _col28, _col3, _col32, _col34, _col36= , _col38, _col39, _col4, _col45, _col48 > Statistics: Num rows: 29784= 102 Data size: 2345958912 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col= 3} {_col4} > 1 {_col1} {_col2} {_col= 3} {_col4} {_col18} {_col20} {_col21} {_col22} {_col32} {_col34} {_col36} {= _col38} {_col39} {_col45} {_col48} > keys: > 0 _col0 (type: int) > 1 _col28 (type: int) > outputColumnNames: _col1,= _col2, _col3, _col4, _col6, _col7, _col8, _col9, _col23, _col25, _col26, _= col27, _col37, _col39, _col41, _col43, _col44, _col50, _col53 > input vertices: > 0 Map 7 > Statistics: Num rows: 327= 62512 Data size: 2580554752 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (typ= e: string), _col2 (type: string), _col23 (type: int), _col25 (type: float),= _col26 (type: float), _col27 (type: float), _col3 (type: string), _col37 (= type: int), _col39 (type: int), _col4 (type: string), _col41 (type: int), _= col43 (type: string), _col44 (type: string), _col50 (type: int), _col53 (ty= pe: string), _col6 (type: string), _col7 (type: string), _col8 (type: strin= g), _col9 (type: string) > outputColumnNames: _col= 1, _col2, _col23, _col25, _col26, _col27, _col3, _col37, _col39, _col4, _co= l41, _col43, _col44, _col50, _col53, _col6, _col7, _col8, _col9 > Statistics: Num rows: 3= 2762512 Data size: 2580554752 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to = 1 > condition expressions= : > 0=20 > 1 {_col1} {_col2} {= _col3} {_col4} {_col6} {_col7} {_col8} {_col9} {_col25} {_col26} {_col27} {= _col37} {_col39} {_col41} {_col43} {_col44} {_col50} {_col53} > keys: > 0 _col0 (type: int) > 1 _col23 (type: int= ) > outputColumnNames: _c= ol2, _col3, _col4, _col5, _col7, _col8, _col9, _col10, _col26, _col27, _col= 28, _col38, _col40, _col42, _col44, _col45, _col51, _col54 > input vertices: > 0 Map 26 > Statistics: Num rows:= 36038764 Data size: 2838610176 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col54= (type: string), _col51 (type: int), _col44 (type: string), _col45 (type: s= tring), _col7 (type: string), _col8 (type: string), _col9 (type: string), _= col10 (type: string), _col2 (type: string), _col3 (type: string), _col4 (ty= pe: string), _col5 (type: string), _col38 (type: int), _col40 (type: int), = _col42 (type: int), _col26 (type: float), _col27 (type: float), _col28 (typ= e: float) > outputColumnNames: = _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col1= 0, _col11, _col12, _col13, _col14, _col15, _col16, _col17 > Statistics: Num row= s: 36038764 Data size: 2838610176 Basic stats: COMPLETE Column stats: NONE > Group By Operator > aggregations: cou= nt(), sum(_col15), sum(_col16), sum(_col17) > keys: _col0 (type= : string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _= col4 (type: string), _col5 (type: string), _col6 (type: string), _col7 (typ= e: string), _col8 (type: string), _col9 (type: string), _col10 (type: strin= g), _col11 (type: string), _col12 (type: int), _col13 (type: int), _col14 (= type: int) > mode: hash > outputColumnNames= : _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _co= l10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18 > Statistics: Num r= ows: 36038764 Data size: 2838610176 Basic stats: COMPLETE Column stats: NON= E > Reduce Output Ope= rator > key expressions= : _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (typ= e: string), _col4 (type: string), _col5 (type: string), _col6 (type: string= ), _col7 (type: string), _col8 (type: string), _col9 (type: string), _col10= (type: string), _col11 (type: string), _col12 (type: int), _col13 (type: i= nt), _col14 (type: int) > sort order: +++= ++++++++++++ > Map-reduce part= ition columns: _col0 (type: string), _col1 (type: int), _col2 (type: string= ), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 = (type: string), _col7 (type: string), _col8 (type: string), _col9 (type: st= ring), _col10 (type: string), _col11 (type: string), _col12 (type: int), _c= ol13 (type: int), _col14 (type: int) > Statistics: Num= rows: 36038764 Data size: 2838610176 Basic stats: COMPLETE Column stats: N= ONE > value expressio= ns: _col15 (type: bigint), _col16 (type: double), _col17 (type: double), _c= ol18 (type: double) > Reducer 12=20 > Reduce Operator Tree: > Group By Operator > aggregations: count(VALUE._col0), sum(VALUE._col1), sum(V= ALUE._col2), sum(VALUE._col3) > keys: KEY._col0 (type: string), KEY._col1 (type: int), KE= Y._col2 (type: string), KEY._col3 (type: string), KEY._col4 (type: string),= KEY._col5 (type: string), KEY._col6 (type: string), KEY._col7 (type: strin= g), KEY._col8 (type: string), KEY._col9 (type: string), KEY._col10 (type: s= tring), KEY._col11 (type: string), KEY._col12 (type: int), KEY._col13 (type= : int), KEY._col14 (type: int) > mode: mergepartial > outputColumnNames: _col0, _col1, _col2, _col3, _col4, _co= l5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _co= l15, _col16, _col17, _col18 > Statistics: Num rows: 18019382 Data size: 1419305088 Basi= c stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: int), _col2 (type: string), _= col3 (type: string), _col12 (type: int), _col15 (type: bigint), _col16 (typ= e: double), _col17 (type: double), _col18 (type: double) > outputColumnNames: _col0, _col1, _col2, _col3, _col4, _= col5, _col6, _col7 > Statistics: Num rows: 18019382 Data size: 1419305088 Ba= sic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: int), _col1 (type: stri= ng), _col2 (type: string) > sort order: +++ > Map-reduce partition columns: _col0 (type: int), _col= 1 (type: string), _col2 (type: string) > Statistics: Num rows: 18019382 Data size: 1419305088 = Basic stats: COMPLETE Column stats: NONE > value expressions: _col3 (type: int), _col4 (type: bi= gint), _col5 (type: double), _col6 (type: double), _col7 (type: double) > Execution mode: vectorized > Reducer 13=20 > Reduce Operator Tree: > Merge Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {VALUE._col0} {KEY.reducesinkkey1} {KEY.reducesinkkey= 2} {VALUE._col1} {VALUE._col2} {VALUE._col3} {VALUE._col4} {VALUE._col5} {V= ALUE._col6} {VALUE._col7} {VALUE._col8} {VALUE._col9} {VALUE._col10} {VALUE= ._col11} {VALUE._col12} {VALUE._col13} > 1 {VALUE._col0} {VALUE._col1} {VALUE._col2} {VALUE._col= 3} {VALUE._col4} > outputColumnNames: _col0, _col2, _col3, _col4, _col5, _co= l6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _c= ol16, _col20, _col21, _col22, _col23, _col24 > Statistics: Num rows: 19821320 Data size: 1561235584 Basi= c stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (_col21 <=3D _col13) (type: boolean) > Statistics: Num rows: 6607106 Data size: 520411808 Basi= c stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col0 (type: string), _col2 (type: strin= g), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6= (type: string), _col7 (type: string), _col8 (type: string), _col9 (type: s= tring), _col10 (type: string), _col11 (type: string), _col12 (type: int), _= col13 (type: bigint), _col14 (type: double), _col15 (type: double), _col16 = (type: double), _col22 (type: double), _col23 (type: double), _col24 (type:= double), _col20 (type: int), _col21 (type: bigint) > outputColumnNames: _col0, _col1, _col2, _col3, _col4,= _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14,= _col15, _col16, _col17, _col18, _col19, _col20 > Statistics: Num rows: 6607106 Data size: 520411808 Ba= sic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col0 (type: string), _col1 (type:= string), _col20 (type: bigint) > sort order: +++ > Statistics: Num rows: 6607106 Data size: 520411808 = Basic stats: COMPLETE Column stats: NONE > value expressions: _col2 (type: string), _col3 (typ= e: string), _col4 (type: string), _col5 (type: string), _col6 (type: string= ), _col7 (type: string), _col8 (type: string), _col9 (type: string), _col10= (type: string), _col11 (type: int), _col12 (type: bigint), _col13 (type: d= ouble), _col14 (type: double), _col15 (type: double), _col16 (type: double)= , _col17 (type: double), _col18 (type: double), _col19 (type: int) > Reducer 14=20 > Reduce Operator Tree: > Select Operator > expressions: KEY.reducesinkkey0 (type: string), KEY.reduc= esinkkey1 (type: string), VALUE._col0 (type: string), VALUE._col1 (type: st= ring), VALUE._col2 (type: string), VALUE._col3 (type: string), VALUE._col4 = (type: string), VALUE._col5 (type: string), VALUE._col6 (type: string), VAL= UE._col7 (type: string), VALUE._col8 (type: string), VALUE._col9 (type: int= ), VALUE._col10 (type: bigint), VALUE._col11 (type: double), VALUE._col12 (= type: double), VALUE._col13 (type: double), VALUE._col14 (type: double), VA= LUE._col15 (type: double), VALUE._col16 (type: double), VALUE._col17 (type:= int), KEY.reducesinkkey2 (type: bigint) > outputColumnNames: _col0, _col1, _col2, _col3, _col4, _co= l5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _co= l15, _col16, _col17, _col18, _col19, _col20 > Statistics: Num rows: 6607106 Data size: 520411808 Basic = stats: COMPLETE Column stats: NONE > File Output Operator > compressed: false > Statistics: Num rows: 6607106 Data size: 520411808 Basi= c stats: COMPLETE Column stats: NONE > table: > input format: org.apache.hadoop.mapred.TextInputFor= mat > output format: org.apache.hadoop.hive.ql.io.HiveIgn= oreKeyTextOutputFormat > serde: org.apache.hadoop.hive.serde2.lazy.LazySimpl= eSerDe > Execution mode: vectorized > Reducer 20=20 > Reduce Operator Tree: > Group By Operator > aggregations: sum(VALUE._col0), sum(VALUE._col1) > keys: KEY._col0 (type: int) > mode: mergepartial > outputColumnNames: _col0, _col1, _col2 > Statistics: Num rows: 39400588 Data size: 5347397120 Basi= c stats: COMPLETE Column stats: NONE > Filter Operator > predicate: (_col1 > (UDFToDouble(2) * _col2)) (type: bo= olean) > Statistics: Num rows: 13133529 Data size: 1782465661 Ba= sic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col0 (type: int) > outputColumnNames: _col0 > Statistics: Num rows: 13133529 Data size: 1782465661 = Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col4} {_col5} {_col7} {_col9} {_col10= } {_col11} {_col16} {_col17} {_col21} {_col23} {_col25} {_col27} {_col28} > 1=20 > keys: > 0 _col1 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col4, _col5, _col7, _col= 9, _col10, _col11, _col16, _col17, _col21, _col23, _col25, _col27, _col28 > input vertices: > 0 Map 33 > Statistics: Num rows: 16812348 Data size: 132423244= 8 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: int), _col10 (type: flo= at), _col11 (type: float), _col16 (type: int), _col17 (type: int), _col21 (= type: int), _col23 (type: int), _col25 (type: int), _col27 (type: string), = _col28 (type: string), _col4 (type: int), _col5 (type: int), _col7 (type: i= nt), _col9 (type: float) > outputColumnNames: _col1, _col10, _col11, _col16,= _col17, _col21, _col23, _col25, _col27, _col28, _col4, _col5, _col7, _col9 > Statistics: Num rows: 16812348 Data size: 1324232= 448 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} > 1 {_col1} {_col5} {_col7} {_col9} {_col10} {_= col11} {_col16} {_col17} {_col21} {_col23} {_col25} {_col27} {_col28} > keys: > 0 _col0 (type: int) > 1 _col4 (type: int) > outputColumnNames: _col1, _col3, _col7, _col9, = _col11, _col12, _col13, _col18, _col19, _col23, _col25, _col27, _col29, _co= l30 > input vertices: > 0 Map 9 > Statistics: Num rows: 18493584 Data size: 14566= 55744 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: int), _col11 (type:= float), _col12 (type: float), _col13 (type: float), _col18 (type: int), _c= ol19 (type: int), _col23 (type: int), _col25 (type: int), _col27 (type: int= ), _col29 (type: string), _col3 (type: int), _col30 (type: string), _col7 (= type: int), _col9 (type: int) > outputColumnNames: _col1, _col11, _col12, _co= l13, _col18, _col19, _col23, _col25, _col27, _col29, _col3, _col30, _col7, = _col9 > Statistics: Num rows: 18493584 Data size: 145= 6655744 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} > 1 {_col1} {_col3} {_col7} {_col9} {_col11= } {_col12} {_col13} {_col19} {_col23} {_col25} {_col27} {_col29} {_col30} > keys: > 0 _col0 (type: int) > 1 _col18 (type: int) > outputColumnNames: _col1, _col3, _col5, _co= l9, _col11, _col13, _col14, _col15, _col21, _col25, _col27, _col29, _col31,= _col32 > input vertices: > 0 Map 44 > Statistics: Num rows: 20342942 Data size: 1= 602321408 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col3} {_col9} {_col11} {_co= l13} {_col14} {_col15} {_col21} {_col25} {_col27} {_col29} {_col31} {_col32= } > 1 {_col0} {_col3} > keys: > 0 _col5 (type: int) > 1 _col0 (type: int) > outputColumnNames: _col1, _col3, _col9, _= col11, _col13, _col14, _col15, _col21, _col25, _col27, _col29, _col31, _col= 32, _col38, _col41 > input vertices: > 1 Map 29 > Statistics: Num rows: 22377236 Data size:= 1762553600 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: int), _col11 = (type: int), _col13 (type: float), _col14 (type: float), _col15 (type: floa= t), _col21 (type: int), _col25 (type: int), _col27 (type: int), _col29 (typ= e: int), _col3 (type: int), _col31 (type: string), _col32 (type: string), _= col38 (type: int), _col41 (type: string), _col9 (type: int) > outputColumnNames: _col1, _col11, _col1= 3, _col14, _col15, _col21, _col25, _col27, _col29, _col3, _col31, _col32, _= col38, _col41, _col9 > Statistics: Num rows: 22377236 Data siz= e: 1762553600 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0=20 > 1 {_col1} {_col9} {_col11} {_col13}= {_col14} {_col15} {_col21} {_col25} {_col27} {_col29} {_col31} {_col32} {_= col38} {_col41} > keys: > 0 _col0 (type: int) > 1 _col3 (type: int) > outputColumnNames: _col2, _col10, _co= l12, _col14, _col15, _col16, _col22, _col26, _col28, _col30, _col32, _col33= , _col39, _col42 > input vertices: > 0 Map 37 > Statistics: Num rows: 24614960 Data s= ize: 1938808960 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col10 (type: int), _c= ol12 (type: int), _col14 (type: float), _col15 (type: float), _col16 (type:= float), _col2 (type: int), _col22 (type: int), _col26 (type: int), _col28 = (type: int), _col30 (type: int), _col32 (type: string), _col33 (type: strin= g), _col39 (type: int), _col42 (type: string) > outputColumnNames: _col10, _col12, = _col14, _col15, _col16, _col2, _col22, _col26, _col28, _col30, _col32, _col= 33, _col39, _col42 > Statistics: Num rows: 24614960 Data= size: 1938808960 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0=20 > 1 {_col10} {_col12} {_col14} {_= col15} {_col16} {_col22} {_col26} {_col28} {_col30} {_col32} {_col33} {_col= 39} {_col42} > keys: > 0 _col0 (type: int) > 1 _col2 (type: int) > outputColumnNames: _col11, _col13= , _col15, _col16, _col17, _col23, _col27, _col29, _col31, _col33, _col34, _= col40, _col43 > input vertices: > 0 Map 17 > Statistics: Num rows: 27076456 Da= ta size: 2132689920 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col11 (type: int)= , _col13 (type: int), _col15 (type: float), _col16 (type: float), _col17 (t= ype: float), _col23 (type: int), _col27 (type: int), _col29 (type: int), _c= ol31 (type: int), _col33 (type: string), _col34 (type: string), _col40 (typ= e: int), _col43 (type: string) > outputColumnNames: _col11, _col= 13, _col15, _col16, _col17, _col23, _col27, _col29, _col31, _col33, _col34,= _col40, _col43 > Statistics: Num rows: 27076456 = Data size: 2132689920 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col3} {= _col4} > 1 {_col13} {_col15} {_col16= } {_col17} {_col23} {_col27} {_col29} {_col31} {_col33} {_col34} {_col40} {= _col43} > keys: > 0 _col0 (type: int) > 1 _col11 (type: int) > outputColumnNames: _col1, _co= l2, _col3, _col4, _col18, _col20, _col21, _col22, _col28, _col32, _col34, _= col36, _col38, _col39, _col45, _col48 > input vertices: > 0 Map 43 > Statistics: Num rows: 2978410= 2 Data size: 2345958912 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (type: s= tring), _col18 (type: int), _col2 (type: string), _col20 (type: float), _co= l21 (type: float), _col22 (type: float), _col28 (type: int), _col3 (type: s= tring), _col32 (type: int), _col34 (type: int), _col36 (type: int), _col38 = (type: string), _col39 (type: string), _col4 (type: string), _col45 (type: = int), _col48 (type: string) > outputColumnNames: _col1, _= col18, _col2, _col20, _col21, _col22, _col28, _col3, _col32, _col34, _col36= , _col38, _col39, _col4, _col45, _col48 > Statistics: Num rows: 29784= 102 Data size: 2345958912 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to 1 > condition expressions: > 0 {_col1} {_col2} {_col= 3} {_col4} > 1 {_col1} {_col2} {_col= 3} {_col4} {_col18} {_col20} {_col21} {_col22} {_col32} {_col34} {_col36} {= _col38} {_col39} {_col45} {_col48} > keys: > 0 _col0 (type: int) > 1 _col28 (type: int) > outputColumnNames: _col1,= _col2, _col3, _col4, _col6, _col7, _col8, _col9, _col23, _col25, _col26, _= col27, _col37, _col39, _col41, _col43, _col44, _col50, _col53 > input vertices: > 0 Map 28 > Statistics: Num rows: 327= 62512 Data size: 2580554752 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col1 (typ= e: string), _col2 (type: string), _col23 (type: int), _col25 (type: float),= _col26 (type: float), _col27 (type: float), _col3 (type: string), _col37 (= type: int), _col39 (type: int), _col4 (type: string), _col41 (type: int), _= col43 (type: string), _col44 (type: string), _col50 (type: int), _col53 (ty= pe: string), _col6 (type: string), _col7 (type: string), _col8 (type: strin= g), _col9 (type: string) > outputColumnNames: _col= 1, _col2, _col23, _col25, _col26, _col27, _col3, _col37, _col39, _col4, _co= l41, _col43, _col44, _col50, _col53, _col6, _col7, _col8, _col9 > Statistics: Num rows: 3= 2762512 Data size: 2580554752 Basic stats: COMPLETE Column stats: NONE > Map Join Operator > condition map: > Inner Join 0 to = 1 > condition expressions= : > 0=20 > 1 {_col1} {_col2} {= _col3} {_col4} {_col6} {_col7} {_col8} {_col9} {_col25} {_col26} {_col27} {= _col37} {_col39} {_col41} {_col43} {_col44} {_col50} {_col53} > keys: > 0 _col0 (type: int) > 1 _col23 (type: int= ) > outputColumnNames: _c= ol2, _col3, _col4, _col5, _col7, _col8, _col9, _col10, _col26, _col27, _col= 28, _col38, _col40, _col42, _col44, _col45, _col51, _col54 > input vertices: > 0 Map 34 > Statistics: Num rows:= 36038764 Data size: 2838610176 Basic stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col54= (type: string), _col51 (type: int), _col44 (type: string), _col45 (type: s= tring), _col7 (type: string), _col8 (type: string), _col9 (type: string), _= col10 (type: string), _col2 (type: string), _col3 (type: string), _col4 (ty= pe: string), _col5 (type: string), _col38 (type: int), _col40 (type: int), = _col42 (type: int), _col26 (type: float), _col27 (type: float), _col28 (typ= e: float) > outputColumnNames: = _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col1= 0, _col11, _col12, _col13, _col14, _col15, _col16, _col17 > Statistics: Num row= s: 36038764 Data size: 2838610176 Basic stats: COMPLETE Column stats: NONE > Group By Operator > aggregations: cou= nt(), sum(_col15), sum(_col16), sum(_col17) > keys: _col0 (type= : string), _col1 (type: int), _col2 (type: string), _col3 (type: string), _= col4 (type: string), _col5 (type: string), _col6 (type: string), _col7 (typ= e: string), _col8 (type: string), _col9 (type: string), _col10 (type: strin= g), _col11 (type: string), _col12 (type: int), _col13 (type: int), _col14 (= type: int) > mode: hash > outputColumnNames= : _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _co= l10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18 > Statistics: Num r= ows: 36038764 Data size: 2838610176 Basic stats: COMPLETE Column stats: NON= E > Reduce Output Ope= rator > key expressions= : _col0 (type: string), _col1 (type: int), _col2 (type: string), _col3 (typ= e: string), _col4 (type: string), _col5 (type: string), _col6 (type: string= ), _col7 (type: string), _col8 (type: string), _col9 (type: string), _col10= (type: string), _col11 (type: string), _col12 (type: int), _col13 (type: i= nt), _col14 (type: int) > sort order: +++= ++++++++++++ > Map-reduce part= ition columns: _col0 (type: string), _col1 (type: int), _col2 (type: string= ), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 = (type: string), _col7 (type: string), _col8 (type: string), _col9 (type: st= ring), _col10 (type: string), _col11 (type: string), _col12 (type: int), _c= ol13 (type: int), _col14 (type: int) > Statistics: Num= rows: 36038764 Data size: 2838610176 Basic stats: COMPLETE Column stats: N= ONE > value expressio= ns: _col15 (type: bigint), _col16 (type: double), _col17 (type: double), _c= ol18 (type: double) > Reducer 21=20 > Reduce Operator Tree: > Group By Operator > aggregations: count(VALUE._col0), sum(VALUE._col1), sum(V= ALUE._col2), sum(VALUE._col3) > keys: KEY._col0 (type: string), KEY._col1 (type: int), KE= Y._col2 (type: string), KEY._col3 (type: string), KEY._col4 (type: string),= KEY._col5 (type: string), KEY._col6 (type: string), KEY._col7 (type: strin= g), KEY._col8 (type: string), KEY._col9 (type: string), KEY._col10 (type: s= tring), KEY._col11 (type: string), KEY._col12 (type: int), KEY._col13 (type= : int), KEY._col14 (type: int) > mode: mergepartial > outputColumnNames: _col0, _col1, _col2, _col3, _col4, _co= l5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _co= l15, _col16, _col17, _col18 > Statistics: Num rows: 18019382 Data size: 1419305088 Basi= c stats: COMPLETE Column stats: NONE > Select Operator > expressions: _col0 (type: string), _col1 (type: int), _= col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (typ= e: string), _col6 (type: string), _col7 (type: string), _col8 (type: string= ), _col9 (type: string), _col10 (type: string), _col11 (type: string), _col= 12 (type: int), _col15 (type: bigint), _col16 (type: double), _col17 (type:= double), _col18 (type: double) > outputColumnNames: _col0, _col1, _col2, _col3, _col4, _= col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _= col15, _col16 > Statistics: Num rows: 18019382 Data size: 1419305088 Ba= sic stats: COMPLETE Column stats: NONE > Reduce Output Operator > key expressions: _col1 (type: int), _col2 (type: stri= ng), _col3 (type: string) > sort order: +++ > Map-reduce partition columns: _col1 (type: int), _col= 2 (type: string), _col3 (type: string) > Statistics: Num rows: 18019382 Data size: 1419305088 = Basic stats: COMPLETE Column stats: NONE > value expressions: _col0 (type: string), _col4 (type:= string), _col5 (type: string), _col6 (type: string), _col7 (type: string),= _col8 (type: string), _col9 (type: string), _col10 (type: string), _col11 = (type: string), _col12 (type: int), _col13 (type: bigint), _col14 (type: do= uble), _col15 (type: double), _col16 (type: double) > Execution mode: vectorized > Stage: Stage-0 > Fetch Operator > limit: -1 > Processor Tree: > ListSink > {code} > Query=20 > {code} > select cs1.product_name ,cs1.store_name ,cs1.store_zip ,cs1.b_street_numb= er ,cs1.b_streen_name ,cs1.b_city > ,cs1.b_zip ,cs1.c_street_number ,cs1.c_street_name ,cs1.c_city ,cs1.= c_zip ,cs1.syear ,cs1.cnt > ,cs1.s1 ,cs1.s2 ,cs1.s3 > ,cs2.s1 ,cs2.s2 ,cs2.s3 ,cs2.syear ,cs2.cnt > from > (select i_product_name as product_name ,i_item_sk as item_sk ,s_store_nam= e as store_name > ,s_zip as store_zip ,ad1.ca_street_number as b_street_number ,ad1.ca= _street_name as b_streen_name > ,ad1.ca_city as b_city ,ad1.ca_zip as b_zip ,ad2.ca_street_number as= c_street_number > ,ad2.ca_street_name as c_street_name ,ad2.ca_city as c_city ,ad2.ca_= zip as c_zip > ,d1.d_year as syear ,d2.d_year as fsyear ,d3.d_year as s2year ,count= (*) as cnt > ,sum(ss_wholesale_cost) as s1 ,sum(ss_list_price) as s2 ,sum(ss_coup= on_amt) as s3 > FROM store_sales > JOIN store_returns ON store_sales.ss_item_sk =3D store_returns.sr= _item_sk and store_sales.ss_ticket_number =3D store_returns.sr_ticket_numbe= r > JOIN customer ON store_sales.ss_customer_sk =3D customer.c_custom= er_sk > JOIN date_dim d1 ON store_sales.ss_sold_date_sk =3D d1.d_date_sk > JOIN date_dim d2 ON customer.c_first_sales_date_sk =3D d2.d_date_= sk=20 > JOIN date_dim d3 ON customer.c_first_shipto_date_sk =3D d3.d_date= _sk > JOIN store ON store_sales.ss_store_sk =3D store.s_store_sk > JOIN customer_demographics cd1 ON store_sales.ss_cdemo_sk=3D cd1.= cd_demo_sk > JOIN customer_demographics cd2 ON customer.c_current_cdemo_sk =3D= cd2.cd_demo_sk > JOIN promotion ON store_sales.ss_promo_sk =3D promotion.p_promo_s= k > JOIN household_demographics hd1 ON store_sales.ss_hdemo_sk =3D hd= 1.hd_demo_sk > JOIN household_demographics hd2 ON customer.c_current_hdemo_sk = =3D hd2.hd_demo_sk > JOIN customer_address ad1 ON store_sales.ss_addr_sk =3D ad1.ca_ad= dress_sk > JOIN customer_address ad2 ON customer.c_current_addr_sk =3D ad2.c= a_address_sk > JOIN income_band ib1 ON hd1.hd_income_band_sk =3D ib1.ib_income_b= and_sk > JOIN income_band ib2 ON hd2.hd_income_band_sk =3D ib2.ib_income_b= and_sk > JOIN item ON store_sales.ss_item_sk =3D item.i_item_sk > JOIN > (select cs_item_sk > ,sum(cs_ext_list_price) as sale,sum(cr_refunded_cash+cr_reversed_= charge+cr_store_credit) as refund > from catalog_sales JOIN catalog_returns > ON catalog_sales.cs_item_sk =3D catalog_returns.cr_item_sk > and catalog_sales.cs_order_number =3D catalog_returns.cr_order_number > group by cs_item_sk > having sum(cs_ext_list_price)>2*sum(cr_refunded_cash+cr_reversed_charge= +cr_store_credit)) cs_ui > ON store_sales.ss_item_sk =3D cs_ui.cs_item_sk > WHERE =20 > cd1.cd_marital_status <> cd2.cd_marital_status and > i_color in ('maroon','burnished','dim','steel','navajo','chocola= te') and > i_current_price between 35 and 35 + 10 and > i_current_price between 35 + 1 and 35 + 15 > group by i_product_name ,i_item_sk ,s_store_name ,s_zip ,ad1.ca_street_nu= mber > ,ad1.ca_street_name ,ad1.ca_city ,ad1.ca_zip ,ad2.ca_street_number > ,ad2.ca_street_name ,ad2.ca_city ,ad2.ca_zip ,d1.d_year ,d2.d_year= ,d3.d_year > ) cs1 > JOIN > (select i_product_name as product_name ,i_item_sk as item_sk ,s_store_nam= e as store_name > ,s_zip as store_zip ,ad1.ca_street_number as b_street_number ,ad1.ca= _street_name as b_streen_name > ,ad1.ca_city as b_city ,ad1.ca_zip as b_zip ,ad2.ca_street_number as= c_street_number > ,ad2.ca_street_name as c_street_name ,ad2.ca_city as c_city ,ad2.ca_= zip as c_zip > ,d1.d_year as syear ,d2.d_year as fsyear ,d3.d_year as s2year ,count= (*) as cnt > ,sum(ss_wholesale_cost) as s1 ,sum(ss_list_price) as s2 ,sum(ss_coup= on_amt) as s3 > FROM store_sales > JOIN store_returns ON store_sales.ss_item_sk =3D store_returns.sr= _item_sk and store_sales.ss_ticket_number =3D store_returns.sr_ticket_numbe= r > JOIN customer ON store_sales.ss_customer_sk =3D customer.c_custom= er_sk > JOIN date_dim d1 ON store_sales.ss_sold_date_sk =3D d1.d_date_sk > JOIN date_dim d2 ON customer.c_first_sales_date_sk =3D d2.d_date_= sk=20 > JOIN date_dim d3 ON customer.c_first_shipto_date_sk =3D d3.d_date= _sk > JOIN store ON store_sales.ss_store_sk =3D store.s_store_sk > JOIN customer_demographics cd1 ON store_sales.ss_cdemo_sk=3D cd1.= cd_demo_sk > JOIN customer_demographics cd2 ON customer.c_current_cdemo_sk =3D= cd2.cd_demo_sk > JOIN promotion ON store_sales.ss_promo_sk =3D promotion.p_promo_s= k > JOIN household_demographics hd1 ON store_sales.ss_hdemo_sk =3D hd= 1.hd_demo_sk > JOIN household_demographics hd2 ON customer.c_current_hdemo_sk = =3D hd2.hd_demo_sk > JOIN customer_address ad1 ON store_sales.ss_addr_sk =3D ad1.ca_ad= dress_sk > JOIN customer_address ad2 ON customer.c_current_addr_sk =3D ad2.c= a_address_sk > JOIN income_band ib1 ON hd1.hd_income_band_sk =3D ib1.ib_income_b= and_sk > JOIN income_band ib2 ON hd2.hd_income_band_sk =3D ib2.ib_income_b= and_sk > JOIN item ON store_sales.ss_item_sk =3D item.i_item_sk > JOIN > (select cs_item_sk > ,sum(cs_ext_list_price) as sale,sum(cr_refunded_cash+cr_reversed_= charge+cr_store_credit) as refund > from catalog_sales JOIN catalog_returns > ON catalog_sales.cs_item_sk =3D catalog_returns.cr_item_sk > and catalog_sales.cs_order_number =3D catalog_returns.cr_order_number > group by cs_item_sk > having sum(cs_ext_list_price)>2*sum(cr_refunded_cash+cr_reversed_charge= +cr_store_credit)) cs_ui > ON store_sales.ss_item_sk =3D cs_ui.cs_item_sk > WHERE =20 > cd1.cd_marital_status <> cd2.cd_marital_status and > i_color in ('maroon','burnished','dim','steel','navajo','chocola= te') and > i_current_price between 35 and 35 + 10 and > i_current_price between 35 + 1 and 35 + 15 > group by i_product_name ,i_item_sk ,s_store_name ,s_zip ,ad1.ca_street_nu= mber > ,ad1.ca_street_name ,ad1.ca_city ,ad1.ca_zip ,ad2.ca_street_number > ,ad2.ca_street_name ,ad2.ca_city ,ad2.ca_zip ,d1.d_year ,d2.d_year= ,d3.d_year > ) cs2 > ON cs1.item_sk=3Dcs2.item_sk > where=20 > cs1.syear =3D 2000 and > cs2.syear =3D 2000 + 1 and > cs2.cnt <=3D cs1.cnt and > cs1.store_name =3D cs2.store_name and > cs1.store_zip =3D cs2.store_zip > order by cs1.product_name ,cs1.store_name ,cs2.cnt > {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332)