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Posted to commits@hudi.apache.org by "sivabalan narayanan (Jira)" <ji...@apache.org> on 2021/06/02 14:49:00 UTC
[jira] [Resolved] (HUDI-1719) hive on spark/mr,Incremental query of
the mor table, the partition field is incorrect
[ https://issues.apache.org/jira/browse/HUDI-1719?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
sivabalan narayanan resolved HUDI-1719.
---------------------------------------
Resolution: Fixed
> hive on spark/mr,Incremental query of the mor table, the partition field is incorrect
> -------------------------------------------------------------------------------------
>
> Key: HUDI-1719
> URL: https://issues.apache.org/jira/browse/HUDI-1719
> Project: Apache Hudi
> Issue Type: Bug
> Components: Hive Integration
> Affects Versions: 0.7.0, 0.8.0
> Environment: spark2.4.5, hadoop 3.1.1, hive 3.1.1
> Reporter: tao meng
> Assignee: tao meng
> Priority: Major
> Labels: pull-request-available, sev:critical, user-support-issues
> Fix For: 0.9.0
>
>
> now hudi use HoodieCombineHiveInputFormat to achieve Incremental query of the mor table.
> when we have some small files in different partitions, HoodieCombineHiveInputFormat will combine those small file readers. HoodieCombineHiveInputFormat build partition field base on the first file reader in it, however now HoodieCombineHiveInputFormat holds other file readers which come from different partitions.
> When switching readers, we should update ioctx
> test env:
> spark2.4.5, hadoop 3.1.1, hive 3.1.1
> test step:
> step1:
> val df = spark.range(0, 10000).toDF("keyid")
> .withColumn("col3", expr("keyid + 10000000"))
> .withColumn("p", lit(0))
> .withColumn("p1", lit(0))
> .withColumn("p2", lit(6))
> .withColumn("a1", lit(Array[String]("sb1", "rz")))
> .withColumn("a2", lit(Array[String]("sb1", "rz")))
> // create hudi table which has three level partitions p,p1,p2
> merge(df, 4, "default", "hive_8b", DataSourceWriteOptions.MOR_TABLE_TYPE_OPT_VAL, op = "bulk_insert")
>
> step2:
> val df = spark.range(0, 10000).toDF("keyid")
> .withColumn("col3", expr("keyid + 10000000"))
> .withColumn("p", lit(0))
> .withColumn("p1", lit(0))
> .withColumn("p2", lit(7))
> .withColumn("a1", lit(Array[String]("sb1", "rz")))
> .withColumn("a2", lit(Array[String]("sb1", "rz")))
> // upsert current table
> merge(df, 4, "default", "hive_8b", DataSourceWriteOptions.MOR_TABLE_TYPE_OPT_VAL, op = "upsert")
> hive beeline:
> set hive.input.format=org.apache.hudi.hadoop.hive.HoodieCombineHiveInputFormat;
> set hoodie.hive_8b.consume.mode=INCREMENTAL;
> set hoodie.hive_8b.consume.max.commits=3;
> set hoodie.hive_8b.consume.start.timestamp=20210325141300; // this timestamp is smaller the earlist commit, so we can query whole commits
> select `p`, `p1`, `p2`,`keyid` from hive_8b_rt where `_hoodie_commit_time`>'20210325141300' and `keyid` < 5;
> query result:
> +-----+----++-------------+
> |p|p1|p2|keyid|
> +-----+----++-------------+
> |0|0|6|0|
> |0|0|6|1|
> |0|0|6|2|
> |0|0|6|3|
> |0|0|6|4|
> |0|0|6|4|
> |0|0|6|0|
> |0|0|6|3|
> |0|0|6|2|
> |0|0|6|1|
> +-----+----++-------------+
> this result is wrong, since the second step we insert new data in table which p2=7, however in the query result we cannot find p2=7, all p2= 6
>
>
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