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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (DRILL-6118) Handle item star columns during project / filter push down and directory pruning
Date Sat, 24 Feb 2018 17:05:00 GMT

    [ https://issues.apache.org/jira/browse/DRILL-6118?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16375674#comment-16375674
] 

ASF GitHub Bot commented on DRILL-6118:
---------------------------------------

Github user amansinha100 commented on the issue:

    https://github.com/apache/drill/pull/1104
  
    @arina-ielchiieva pls rebase on latest master. 


> Handle item star columns during project  /  filter push down and directory pruning
> ----------------------------------------------------------------------------------
>
>                 Key: DRILL-6118
>                 URL: https://issues.apache.org/jira/browse/DRILL-6118
>             Project: Apache Drill
>          Issue Type: Improvement
>    Affects Versions: 1.12.0
>            Reporter: Arina Ielchiieva
>            Assignee: Arina Ielchiieva
>            Priority: Major
>              Labels: doc-impacting, ready-to-commit
>             Fix For: 1.13.0
>
>
> Project push down, filter push down and partition pruning does not work with dynamically
expanded column with is represented as star in ITEM operator: _ITEM($0, 'column_name')_ where
$0 is a star.
>  This often occurs when view, sub-select or cte with star is issued.
>  To solve this issue we can create {{DrillFilterItemStarReWriterRule}} which will rewrite
such ITEM operator before filter push down and directory pruning. For project into scan push
down logic will be handled separately in already existing rule {{DrillPushProjectIntoScanRule}}.
Basically, we can consider the following queries the same: 
>  {{select col1 from t}}
>  {{select col1 from (select * from t)}}
> *Use cases*
> Since item star columns where not considered during project / filter push down and directory
pruning, push down and pruning did not happen. This was causing Drill to read all columns
from file (when only several are needed) or ready all files instead. Views with star query
is the most common example. Such behavior significantly degrades performance for item star
queries comparing to queries without item star.
> *EXAMPLES*
> *Data set* 
> will create table with three files each in dedicated sub-folder:
> {noformat}
> use dfs.tmp;
> create table `order_ctas/t1` as select cast(o_orderdate as date) as o_orderdate from
cp.`tpch/orders.parquet` where o_orderdate between date '1992-01-01' and date '1992-01-03';
> create table `order_ctas/t2` as select cast(o_orderdate as date) as o_orderdate from
cp.`tpch/orders.parquet` where o_orderdate between date '1992-01-04' and date '1992-01-06';
> create table `order_ctas/t3` as select cast(o_orderdate as date) as o_orderdate from
cp.`tpch/orders.parquet` where o_orderdate between date '1992-01-07' and date '1992-01-09';
> {noformat}
> *Filter push down*
> {{select * from order_ctas where o_orderdate = date '1992-01-01'}} will read only one
file
> {noformat}
> 00-00    Screen
> 00-01      Project(**=[$0])
> 00-02        Project(T1¦¦**=[$0])
> 00-03          SelectionVectorRemover
> 00-04            Filter(condition=[=($1, 1992-01-01)])
> 00-05              Project(T1¦¦**=[$0], o_orderdate=[$1])
> 00-06                Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath [path=/tmp/order_ctas/t1/0_0_0.parquet]],
selectionRoot=/tmp/order_ctas, numFiles=1, numRowGroups=1, usedMetadataFile=false, columns=[`**`]]])
> {noformat}
> {{select * from (select * from order_ctas) where o_orderdate = date '1992-01-01'}} will
ready all three files
> {noformat}
> 00-00    Screen
> 00-01      Project(**=[$0])
> 00-02        SelectionVectorRemover
> 00-03          Filter(condition=[=(ITEM($0, 'o_orderdate'), 1992-01-01)])
> 00-04            Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath [path=/tmp/order_ctas/t1/0_0_0.parquet],
ReadEntryWithPath [path=/tmp/order_ctas/t2/0_0_0.parquet], ReadEntryWithPath [path=/tmp/order_ctas/t3/0_0_0.parquet]],
selectionRoot=/tmp/order_ctas, numFiles=3, numRowGroups=3, usedMetadataFile=false, columns=[`**`]]])
> {noformat}
> *Directory pruning*
> {{select * from order_ctas where dir0 = 't1'}} will read data only from one folder
> {noformat}
> 00-00    Screen
> 00-01      Project(**=[$0])
> 00-02        Project(**=[$0])
> 00-03          Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath [path=/tmp/order_ctas/t1/0_0_0.parquet]],
selectionRoot=/tmporder_ctas, numFiles=1, numRowGroups=1, usedMetadataFile=false, columns=[`**`]]])
> {noformat}
> {{select * from (select * from order_ctas) where dir0 = 't1'}} will read content of all
three folders
> {noformat}
> 00-00    Screen
> 00-01      Project(**=[$0])
> 00-02        SelectionVectorRemover
> 00-03          Filter(condition=[=(ITEM($0, 'dir0'), 't1')])
> 00-04            Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath [path=/tmp/order_ctas/t1/0_0_0.parquet],
ReadEntryWithPath [path=/tmp/order_ctas/t2/0_0_0.parquet], ReadEntryWithPath [path=/tmp/order_ctas/t3/0_0_0.parquet]],
selectionRoot=/tmp/order_ctas, numFiles=3, numRowGroups=3, usedMetadataFile=false, columns=[`**`]]])
> {noformat}
> *Project into Scan push down*
> {{select o_orderdate, count(1) from order_ctas group by o_orderdate}} will ready only
one column from the files
> {noformat}
> 00-00    Screen
> 00-01      Project(o_orderdate=[$0], EXPR$1=[$1])
> 00-02        HashAgg(group=[{0}], EXPR$1=[COUNT()])
> 00-03          Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath [path=/tmp/order_ctas/t1/0_0_0.parquet],
ReadEntryWithPath [path=/tmp/order_ctas/t2/0_0_0.parquet], ReadEntryWithPath [path=/tmp/order_ctas/t3/0_0_0.parquet]],
selectionRoot=/tmp/order_ctas, numFiles=3, numRowGroups=3, usedMetadataFile=false, columns=[`o_orderdate`]]])
> {noformat}
> {{select o_orderdate, count(1) from (select * from order_ctas) group by o_orderdate}}
will ready all columns from the files
> {noformat}
> 00-00    Screen
> 00-01      Project(col_vrchr=[$0], EXPR$1=[$1])
> 00-02        StreamAgg(group=[{0}], EXPR$1=[COUNT()])
> 00-03          Sort(sort0=[$0], dir0=[ASC])
> 00-04            Project(col_vrchr=[ITEM($0, 'o_orderdate')])
> 00-05         Scan(groupscan=[ParquetGroupScan [entries=[ReadEntryWithPath [path=/tmp/order_ctas/t1/0_0_0.parquet],
ReadEntryWithPath [path=/tmp/order_ctas/t2/0_0_0.parquet], ReadEntryWithPath [path=/tmp/order_ctas/t3/0_0_0.parquet]],
selectionRoot=/tmp/order_ctas, numFiles=3, numRowGroups=3, usedMetadataFile=false, columns=[`**`]]])
> {noformat}
> This Jira aims to fix all three described cases above in order to improve performance
for queries with item star columns.
>  



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