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https://issues.apache.org/jira/browse/HIVE-18553?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16363373#comment-16363373
 ] 

Vihang Karajgaonkar commented on HIVE-18553:
--------------------------------------------

+1 (pending tests) LGTM.

> Support schema evolution in Parquet Vectorization reader
> --------------------------------------------------------
>
>                 Key: HIVE-18553
>                 URL: https://issues.apache.org/jira/browse/HIVE-18553
>             Project: Hive
>          Issue Type: Sub-task
>    Affects Versions: 3.0.0, 2.4.0, 2.3.2
>            Reporter: Vihang Karajgaonkar
>            Assignee: Ferdinand Xu
>            Priority: Major
>         Attachments: HIVE-18553.10.patch, HIVE-18553.11.patch, 
> HIVE-18553.2.patch, HIVE-18553.3.patch, HIVE-18553.4.patch, 
> HIVE-18553.5.patch, HIVE-18553.6.patch, HIVE-18553.7.patch, 
> HIVE-18553.8.patch, HIVE-18553.9.patch, HIVE-18553.patch, 
> test_result_based_on_HIVE-18553.xlsx
>
>
> For schema evolution, it includes the following points:
> 1. column changes
>     column reorder
>     column add, column delete
>     column rename
> 2. type conversion
>     low precision to high precision
>     type to String
> For 1st type, current the code is not supporting the column addition 
> operation. Detailed error is as follows:
> {code}
> 0: jdbc:hive2://localhost:10000/default> desc test_p;
> +-----------+------------+----------+
> | col_name  | data_type  | comment  |
> +-----------+------------+----------+
> | t1        | tinyint    |          |
> | t2        | tinyint    |          |
> | i1        | int        |          |
> | i2        | int        |          |
> +-----------+------------+----------+
> 0: jdbc:hive2://localhost:10000/default> set hive.fetch.task.conversion=none;
> 0: jdbc:hive2://localhost:10000/default> set 
> hive.vectorized.execution.enabled=true;
> 0: jdbc:hive2://localhost:10000/default> alter table test_p add columns (ts 
> timestamp);
> 0: jdbc:hive2://localhost:10000/default> select * from test_p;
> Error: Error while processing statement: FAILED: Execution Error, return code 
> 2 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask (state=08S01,code=2)
> {code}
> Following exception is seen in the logs
> {code}
> Caused by: java.lang.IllegalArgumentException: [ts] BINARY is not in the 
> store: [[i1] INT32, [i2] INT32, [t1] INT32, [t2] INT32] 3
>         at 
> org.apache.parquet.hadoop.ColumnChunkPageReadStore.getPageReader(ColumnChunkPageReadStore.java:160)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.hive.ql.io.parquet.vector.VectorizedParquetRecordReader.buildVectorizedParquetReader(VectorizedParquetRecordReader.java:479)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.hive.ql.io.parquet.vector.VectorizedParquetRecordReader.checkEndOfRowGroup(VectorizedParquetRecordReader.java:432)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.hive.ql.io.parquet.vector.VectorizedParquetRecordReader.nextBatch(VectorizedParquetRecordReader.java:393)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.hive.ql.io.parquet.vector.VectorizedParquetRecordReader.next(VectorizedParquetRecordReader.java:345)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.hive.ql.io.parquet.vector.VectorizedParquetRecordReader.next(VectorizedParquetRecordReader.java:88)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.hive.ql.io.HiveContextAwareRecordReader.doNext(HiveContextAwareRecordReader.java:360)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.hive.ql.io.CombineHiveRecordReader.doNext(CombineHiveRecordReader.java:167)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.hive.ql.io.CombineHiveRecordReader.doNext(CombineHiveRecordReader.java:52)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.hive.ql.io.HiveContextAwareRecordReader.next(HiveContextAwareRecordReader.java:116)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.hive.shims.HadoopShimsSecure$CombineFileRecordReader.doNextWithExceptionHandler(HadoopShimsSecure.java:229)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.hive.shims.HadoopShimsSecure$CombineFileRecordReader.next(HadoopShimsSecure.java:142)
>  ~[hive-exec-3.0.0-SNAPSHOT.jar:3.0.0-SNAPSHOT]
>         at 
> org.apache.hadoop.mapred.MapTask$TrackedRecordReader.moveToNext(MapTask.java:199)
>  ~[hadoop-mapreduce-client-core-3.0.0-alpha3-cdh6.x-SNAPSHOT.jar:?]
>         at 
> org.apache.hadoop.mapred.MapTask$TrackedRecordReader.next(MapTask.java:185) 
> ~[hadoop-mapreduce-client-core-3.0.0-alpha3-cdh6.x-SNAPSHOT.jar:?]
>         at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:52) 
> ~[hadoop-mapreduce-client-core-3.0.0-alpha3-cdh6.x-SNAPSHOT.jar:?]
>         at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:459) 
> ~[hadoop-mapreduce-client-core-3.0.0-alpha3-cdh6.x-SNAPSHOT.jar:?]
>         at org.apache.hadoop.mapred.MapTask.run(MapTask.java:343) 
> ~[hadoop-mapreduce-client-core-3.0.0-alpha3-cdh6.x-SNAPSHOT.jar:?]
>         at 
> org.apache.hadoop.mapred.LocalJobRunner$Job$MapTaskRunnable.run(LocalJobRunner.java:271)
>  ~[hadoop-mapreduce-client-common-3.0.0-alpha3-cdh6.x-SNAPSHOT.jar:?]
>         at 
> java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) 
> ~[?:1.8.0_121]
>         at java.util.concurrent.FutureTask.run(FutureTask.java:266) 
> ~[?:1.8.0_121]
>         at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
>  ~[?:1.8.0_121]
>         at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
>  ~[?:1.8.0_121]
>         at java.lang.Thread.run(Thread.java:745) ~[?:1.8.0_121]
> {code}
> For 2nd type operation, non Vectorized Parquet reader leverages existing 
> Parquet String inspector to do the conversion while vectorized path does not.
> To support, this JIRA is providing an abstract layer to read the underlying 
> data and convert it to what Hive required for further computing.



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