From dev-return-58908-archive-asf-public=cust-asf.ponee.io@phoenix.apache.org Fri Dec 6 03:57:03 2019 Return-Path: X-Original-To: archive-asf-public@cust-asf.ponee.io Delivered-To: archive-asf-public@cust-asf.ponee.io Received: from mail.apache.org (hermes.apache.org [207.244.88.153]) by mx-eu-01.ponee.io (Postfix) with SMTP id C7E4C18065B for ; Fri, 6 Dec 2019 04:57:02 +0100 (CET) Received: (qmail 51884 invoked by uid 500); 6 Dec 2019 03:57:01 -0000 Mailing-List: contact dev-help@phoenix.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: dev@phoenix.apache.org Delivered-To: mailing list dev@phoenix.apache.org Received: (qmail 51854 invoked by uid 99); 6 Dec 2019 03:57:01 -0000 Received: from mailrelay1-us-west.apache.org (HELO mailrelay1-us-west.apache.org) (209.188.14.139) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 06 Dec 2019 03:57:01 +0000 Received: from jira-he-de.apache.org (static.172.67.40.188.clients.your-server.de [188.40.67.172]) by mailrelay1-us-west.apache.org (ASF Mail Server at mailrelay1-us-west.apache.org) with ESMTP id B7EF8E2DEB for ; Fri, 6 Dec 2019 03:57:00 +0000 (UTC) Received: from jira-he-de.apache.org (localhost.localdomain [127.0.0.1]) by jira-he-de.apache.org (ASF Mail Server at jira-he-de.apache.org) with ESMTP id 1DB7E7802BF for ; Fri, 6 Dec 2019 03:57:00 +0000 (UTC) Date: Fri, 6 Dec 2019 03:57:00 +0000 (UTC) From: "Aritra Nayak (Jira)" To: dev@phoenix.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Updated] (PHOENIX-5361) FileNotFoundException found when schema is in lowercase 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/PHOENIX-5361?page=3Dcom.atlass= ian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aritra Nayak updated PHOENIX-5361: ---------------------------------- Description:=20 The table name (DUMMY_DATA) is in uppercase, but the schema name (s01) is i= n lowercase. =C2=A0 Steps to reproduce: 1. Create the Hive table: {code:java} CREATE TABLE IF NOT EXISTS "s01"."DUMMY_DATA"("id" BIGINT BIGINT PRIMARY KE= Y, "firstName" VARCHAR, "lastName" VARCHAR); {code} 2. Upload the CSV file in your preferred HDFS location{code} {code:java} /data/s01/DUMMY_DATA/1.csv{code} 3. Run the hadoop jar command to bulk upload{code} {code:java} hadoop jar /opt/phoenix/phoenix4.13-cdh5.9.2-marin-1.5.1/phoenix4.13-cdh5.9= .2-marin-1.5.1-client.jar org.apache.phoenix.mapreduce.CsvBulkLoadTool --s = \"\"s01\"\" --t DUMMY_DATA --input /data/s01/DUMMY_DATA/1.csv --zookeeper z= k-journalnode-lv-101:2181 {code} Getting the below error: {code:java} Exception in thread "main" java.io.FileNotFoundException: Bulkload dir /tmp= /94ea4875-3453-4ed6-823d-3544ff05fd56/s01.DUMMY_DATA not found =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFil= es.visitBulkHFiles(LoadIncrementalHFiles.java:194) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFil= es.discoverLoadQueue(LoadIncrementalHFiles.java:289) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFil= es.doBulkLoad(LoadIncrementalHFiles.java:393) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFil= es.doBulkLoad(LoadIncrementalHFiles.java:339) =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.com= pletebulkload(AbstractBulkLoadTool.java:355) =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.sub= mitJob(AbstractBulkLoadTool.java:332) =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.loa= dData(AbstractBulkLoadTool.java:270) =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.run= (AbstractBulkLoadTool.java:183) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java= :70) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java= :84) =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.CsvBulkLoadTool.main(Csv= BulkLoadTool.java:109) =C2=A0=C2=A0 =C2=A0at sun.reflect.NativeMethodAccessorImpl.invoke0(Native M= ethod) =C2=A0=C2=A0 =C2=A0at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMet= hodAccessorImpl.java:62) =C2=A0=C2=A0 =C2=A0at sun.reflect.DelegatingMethodAccessorImpl.invoke(Deleg= atingMethodAccessorImpl.java:43) =C2=A0=C2=A0 =C2=A0at java.lang.reflect.Method.invoke(Method.java:498) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.RunJar.run(RunJar.java:221) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.RunJar.main(RunJar.java:136) {code} =C2=A0 The Map Reduce job reads 100_000 records, but does not write any =C2=A0 {code:java} 19/06/18 20:06:24 INFO mapreduce.Job: Counters: 50 =C2=A0=C2=A0 =C2=A0File System Counters =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of bytes read=3D20 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of bytes written=3D31580= 1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of read operations=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of large read operations= =3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of write operations=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of bytes read=3D41666811 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of bytes written=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of read operations=3D4 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of large read operations= =3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of write operations=3D0 =C2=A0=C2=A0 =C2=A0Job Counters =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Launched map tasks=3D1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Launched reduce tasks=3D1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Data-local map tasks=3D1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all maps in occup= ied slots (ms)=3D39894 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all reduces in oc= cupied slots (ms)=3D56216 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all map tasks (ms= )=3D19947 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all reduce tasks = (ms)=3D14054 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total vcore-seconds taken by all map = tasks=3D19947 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total vcore-seconds taken by all redu= ce tasks=3D14054 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total megabyte-seconds taken by all m= ap tasks=3D40851456 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total megabyte-seconds taken by all r= educe tasks=3D57565184 =C2=A0=C2=A0 =C2=A0Map-Reduce Framework =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map input records=3D1000000 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map output records=3D0 <----- see h= ere =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map output bytes=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map output materialized bytes=3D16 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Input split bytes=3D123 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Combine input records=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Combine output records=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce input groups=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce shuffle bytes=3D16 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce input records=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce output records=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Spilled Records=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Shuffled Maps =3D1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Failed Shuffles=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Merged Map outputs=3D1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0GC time elapsed (ms)=3D914 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0CPU time spent (ms)=3D49240 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Physical memory (bytes) snapshot=3D20= 22809600 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Virtual memory (bytes) snapshot=3D806= 4647168 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total committed heap usage (bytes)=3D= 3589275648 =C2=A0=C2=A0 =C2=A0Phoenix MapReduce Import =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Upserts Done=3D1000000 =C2=A0=C2=A0 =C2=A0Shuffle Errors =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0BAD_ID=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0CONNECTION=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0IO_ERROR=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0WRONG_LENGTH=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0WRONG_MAP=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0WRONG_REDUCE=3D0 =C2=A0=C2=A0 =C2=A0File Input Format Counters =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Bytes Read=3D41666688 =C2=A0=C2=A0 =C2=A0File Output Format Counters =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Bytes Written=3D0 {code} =C2=A0=C2=A0 {color:#14892c}Same steps (1-3) when followed with schema name= S01, passes and data gets successfully uploaded into the table{color} was: The table name (DUMMY_DATA) is in uppercase, but the schema name (s01) is i= n lowercase. =C2=A0 Steps to reproduce: # Create the Hive table: {code:java} CREATE TABLE IF NOT EXISTS "s01"."DUMMY_DATA"("id" BIGINT BIGINT PRIMARY KE= Y, "firstName" VARCHAR, "lastName" VARCHAR); {code} # Upload the CSV file in your preferred HDFS location{code} {code:java} /data/s01/DUMMY_DATA/1.csv{code} # Run the hadoop jar command to bulk upload{code} {code:java} hadoop jar /opt/phoenix/phoenix4.13-cdh5.9.2-marin-1.5.1/phoenix4.13-cdh5.9= .2-marin-1.5.1-client.jar org.apache.phoenix.mapreduce.CsvBulkLoadTool --s = \"\"s01\"\" --t DUMMY_DATA --input /data/s01/DUMMY_DATA/1.csv --zookeeper z= k-journalnode-lv-101:2181 {code} Getting the below error: {code:java} Exception in thread "main" java.io.FileNotFoundException: Bulkload dir /tmp= /94ea4875-3453-4ed6-823d-3544ff05fd56/s01.DUMMY_DATA not found =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFil= es.visitBulkHFiles(LoadIncrementalHFiles.java:194) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFil= es.discoverLoadQueue(LoadIncrementalHFiles.java:289) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFil= es.doBulkLoad(LoadIncrementalHFiles.java:393) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFil= es.doBulkLoad(LoadIncrementalHFiles.java:339) =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.com= pletebulkload(AbstractBulkLoadTool.java:355) =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.sub= mitJob(AbstractBulkLoadTool.java:332) =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.loa= dData(AbstractBulkLoadTool.java:270) =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.run= (AbstractBulkLoadTool.java:183) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java= :70) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java= :84) =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.CsvBulkLoadTool.main(Csv= BulkLoadTool.java:109) =C2=A0=C2=A0 =C2=A0at sun.reflect.NativeMethodAccessorImpl.invoke0(Native M= ethod) =C2=A0=C2=A0 =C2=A0at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMet= hodAccessorImpl.java:62) =C2=A0=C2=A0 =C2=A0at sun.reflect.DelegatingMethodAccessorImpl.invoke(Deleg= atingMethodAccessorImpl.java:43) =C2=A0=C2=A0 =C2=A0at java.lang.reflect.Method.invoke(Method.java:498) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.RunJar.run(RunJar.java:221) =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.RunJar.main(RunJar.java:136) {code} =C2=A0 The Map Reduce job reads 100_000 records, but does not write any =C2=A0 {code:java} 19/06/18 20:06:24 INFO mapreduce.Job: Counters: 50 =C2=A0=C2=A0 =C2=A0File System Counters =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of bytes read=3D20 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of bytes written=3D31580= 1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of read operations=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of large read operations= =3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of write operations=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of bytes read=3D41666811 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of bytes written=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of read operations=3D4 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of large read operations= =3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of write operations=3D0 =C2=A0=C2=A0 =C2=A0Job Counters =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Launched map tasks=3D1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Launched reduce tasks=3D1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Data-local map tasks=3D1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all maps in occup= ied slots (ms)=3D39894 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all reduces in oc= cupied slots (ms)=3D56216 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all map tasks (ms= )=3D19947 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all reduce tasks = (ms)=3D14054 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total vcore-seconds taken by all map = tasks=3D19947 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total vcore-seconds taken by all redu= ce tasks=3D14054 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total megabyte-seconds taken by all m= ap tasks=3D40851456 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total megabyte-seconds taken by all r= educe tasks=3D57565184 =C2=A0=C2=A0 =C2=A0Map-Reduce Framework =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map input records=3D1000000 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map output records=3D0 <----- see h= ere =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map output bytes=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map output materialized bytes=3D16 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Input split bytes=3D123 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Combine input records=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Combine output records=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce input groups=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce shuffle bytes=3D16 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce input records=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce output records=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Spilled Records=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Shuffled Maps =3D1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Failed Shuffles=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Merged Map outputs=3D1 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0GC time elapsed (ms)=3D914 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0CPU time spent (ms)=3D49240 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Physical memory (bytes) snapshot=3D20= 22809600 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Virtual memory (bytes) snapshot=3D806= 4647168 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total committed heap usage (bytes)=3D= 3589275648 =C2=A0=C2=A0 =C2=A0Phoenix MapReduce Import =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Upserts Done=3D1000000 =C2=A0=C2=A0 =C2=A0Shuffle Errors =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0BAD_ID=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0CONNECTION=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0IO_ERROR=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0WRONG_LENGTH=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0WRONG_MAP=3D0 =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0WRONG_REDUCE=3D0 =C2=A0=C2=A0 =C2=A0File Input Format Counters =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Bytes Read=3D41666688 =C2=A0=C2=A0 =C2=A0File Output Format Counters =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Bytes Written=3D0 {code} =C2=A0=C2=A0 {color:#14892c}Same steps (1-3) when followed with schema name= S01, passes and data gets successfully uploaded into the table{color} > FileNotFoundException found when schema is in lowercase > ------------------------------------------------------- > > Key: PHOENIX-5361 > URL: https://issues.apache.org/jira/browse/PHOENIX-5361 > Project: Phoenix > Issue Type: Bug > Affects Versions: 4.13.0 > Environment: *Hadoop*: 2.6.0-cdh5.9.2 > *Phoenix*: 4.13 > *HBase*: 1.2.0-cdh5.9.2 > *Java*: 8 > Reporter: Aritra Nayak > Priority: Major > > The table name (DUMMY_DATA) is in uppercase, but the schema name (s01) is= in lowercase. > =C2=A0 > Steps to reproduce: > 1. Create the Hive table: > {code:java} > CREATE TABLE IF NOT EXISTS "s01"."DUMMY_DATA"("id" BIGINT BIGINT PRIMARY = KEY, "firstName" VARCHAR, "lastName" VARCHAR); > {code} > 2. Upload the CSV file in your preferred HDFS location{code} > {code:java} > /data/s01/DUMMY_DATA/1.csv{code} > 3. Run the hadoop jar command to bulk upload{code} > {code:java} > hadoop jar /opt/phoenix/phoenix4.13-cdh5.9.2-marin-1.5.1/phoenix4.13-cdh5= .9.2-marin-1.5.1-client.jar org.apache.phoenix.mapreduce.CsvBulkLoadTool --= s \"\"s01\"\" --t DUMMY_DATA --input /data/s01/DUMMY_DATA/1.csv --zookeeper= zk-journalnode-lv-101:2181 > {code} > Getting the below error: > {code:java} > Exception in thread "main" java.io.FileNotFoundException: Bulkload dir /t= mp/94ea4875-3453-4ed6-823d-3544ff05fd56/s01.DUMMY_DATA not found > =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHF= iles.visitBulkHFiles(LoadIncrementalHFiles.java:194) > =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHF= iles.discoverLoadQueue(LoadIncrementalHFiles.java:289) > =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHF= iles.doBulkLoad(LoadIncrementalHFiles.java:393) > =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.hbase.mapreduce.LoadIncrementalHF= iles.doBulkLoad(LoadIncrementalHFiles.java:339) > =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.c= ompletebulkload(AbstractBulkLoadTool.java:355) > =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.s= ubmitJob(AbstractBulkLoadTool.java:332) > =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.l= oadData(AbstractBulkLoadTool.java:270) > =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.AbstractBulkLoadTool.r= un(AbstractBulkLoadTool.java:183) > =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.ToolRunner.run(ToolRunner.ja= va:70) > =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.ToolRunner.run(ToolRunner.ja= va:84) > =C2=A0=C2=A0 =C2=A0at org.apache.phoenix.mapreduce.CsvBulkLoadTool.main(C= svBulkLoadTool.java:109) > =C2=A0=C2=A0 =C2=A0at sun.reflect.NativeMethodAccessorImpl.invoke0(Native= Method) > =C2=A0=C2=A0 =C2=A0at sun.reflect.NativeMethodAccessorImpl.invoke(NativeM= ethodAccessorImpl.java:62) > =C2=A0=C2=A0 =C2=A0at sun.reflect.DelegatingMethodAccessorImpl.invoke(Del= egatingMethodAccessorImpl.java:43) > =C2=A0=C2=A0 =C2=A0at java.lang.reflect.Method.invoke(Method.java:498) > =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.RunJar.run(RunJar.java:221) > =C2=A0=C2=A0 =C2=A0at org.apache.hadoop.util.RunJar.main(RunJar.java:136) > {code} > =C2=A0 The Map Reduce job reads 100_000 records, but does not write any > =C2=A0 > {code:java} > 19/06/18 20:06:24 INFO mapreduce.Job: Counters: 50 > =C2=A0=C2=A0 =C2=A0File System Counters > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of bytes read=3D20 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of bytes written=3D315= 801 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of read operations=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of large read operatio= ns=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0FILE: Number of write operations=3D= 0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of bytes read=3D416668= 11 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of bytes written=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of read operations=3D4 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of large read operatio= ns=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0HDFS: Number of write operations=3D= 0 > =C2=A0=C2=A0 =C2=A0Job Counters > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Launched map tasks=3D1 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Launched reduce tasks=3D1 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Data-local map tasks=3D1 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all maps in occ= upied slots (ms)=3D39894 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all reduces in = occupied slots (ms)=3D56216 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all map tasks (= ms)=3D19947 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total time spent by all reduce task= s (ms)=3D14054 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total vcore-seconds taken by all ma= p tasks=3D19947 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total vcore-seconds taken by all re= duce tasks=3D14054 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total megabyte-seconds taken by all= map tasks=3D40851456 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total megabyte-seconds taken by all= reduce tasks=3D57565184 > =C2=A0=C2=A0 =C2=A0Map-Reduce Framework > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map input records=3D1000000 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map output records=3D0 <----- see= here > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map output bytes=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Map output materialized bytes=3D16 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Input split bytes=3D123 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Combine input records=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Combine output records=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce input groups=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce shuffle bytes=3D16 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce input records=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Reduce output records=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Spilled Records=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Shuffled Maps =3D1 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Failed Shuffles=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Merged Map outputs=3D1 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0GC time elapsed (ms)=3D914 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0CPU time spent (ms)=3D49240 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Physical memory (bytes) snapshot=3D= 2022809600 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Virtual memory (bytes) snapshot=3D8= 064647168 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Total committed heap usage (bytes)= =3D3589275648 > =C2=A0=C2=A0 =C2=A0Phoenix MapReduce Import > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Upserts Done=3D1000000 > =C2=A0=C2=A0 =C2=A0Shuffle Errors > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0BAD_ID=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0CONNECTION=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0IO_ERROR=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0WRONG_LENGTH=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0WRONG_MAP=3D0 > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0WRONG_REDUCE=3D0 > =C2=A0=C2=A0 =C2=A0File Input Format Counters > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Bytes Read=3D41666688 > =C2=A0=C2=A0 =C2=A0File Output Format Counters > =C2=A0=C2=A0 =C2=A0=C2=A0=C2=A0 =C2=A0Bytes Written=3D0 > {code} > =C2=A0=C2=A0 {color:#14892c}Same steps (1-3) when followed with schema na= me S01, passes and data gets successfully uploaded into the table{color} -- This message was sent by Atlassian Jira (v8.3.4#803005)