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https://issues.apache.org/jira/browse/HUDI-2058?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17374056#comment-17374056
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ASF GitHub Bot commented on HUDI-2058:
--------------------------------------
hudi-bot edited a comment on pull request #3139:
URL: https://github.com/apache/hudi/pull/3139#issuecomment-866671675
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## CI report:
* 42066935f5571aad75be3d27ba3321b6e61f4b22 Azure:
[FAILURE](https://dev.azure.com/apache-hudi-ci-org/785b6ef4-2f42-4a89-8f0e-5f0d7039a0cc/_build/results?buildId=424)
* f189b69eb1d47720891a49f76c3e6edf3d9cf557 UNKNOWN
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> support incremental query for insert_overwrite_table/insert_overwrite
> operation on cow table
> --------------------------------------------------------------------------------------------
>
> Key: HUDI-2058
> URL: https://issues.apache.org/jira/browse/HUDI-2058
> Project: Apache Hudi
> Issue Type: Bug
> Components: Incremental Pull
> Affects Versions: 0.8.0
> Environment: hadoop 3.1.1
> spark3.1.1
> hive 3.1.1
> Reporter: tao meng
> Assignee: tao meng
> Priority: Major
> Labels: pull-request-available
> Fix For: 0.9.0
>
>
> when incremental query contains multiple commit before and after
> replacecommit, and the query result contains the data of the old file.
> Notice: mor table is ok, only cow table has this problem.
>
> when query incr_view for cow table, replacecommit is ignored which lead the
> wrong result.
>
>
> test step:
> step1: create dataFrame
> val df = spark.range(0, 10).toDF("keyid")
> .withColumn("col3", expr("keyid"))
> .withColumn("age", lit(1))
> .withColumn("p", lit(2))
>
> step2: insert df to a empty hoodie table
> df.write.format("hudi").
> option(DataSourceWriteOptions.TABLE_TYPE_OPT_KEY,
> DataSourceWriteOptions.COW_TABLE_TYPE_OPT_VAL).
> option(DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY, "col3").
> option(DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY, "keyid").
> option(DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY, "").
> option(DataSourceWriteOptions.KEYGENERATOR_CLASS_OPT_KEY,
> "org.apache.hudi.keygen.NonpartitionedKeyGenerator").
> option(DataSourceWriteOptions.OPERATION_OPT_KEY, "insert").
> option("hoodie.insert.shuffle.parallelism", "4").
> option(HoodieWriteConfig.TABLE_NAME, "hoodie_test")
> .mode(SaveMode.Overwrite).save(basePath)
>
> step3: do insert_overwrite
> df.write.format("hudi").
> option(DataSourceWriteOptions.TABLE_TYPE_OPT_KEY,
> DataSourceWriteOptions.COW_TABLE_TYPE_OPT_VAL).
> option(DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY, "col3").
> option(DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY, "keyid").
> option(DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY, "").
> option(DataSourceWriteOptions.KEYGENERATOR_CLASS_OPT_KEY,
> "org.apache.hudi.keygen.NonpartitionedKeyGenerator").
> option(DataSourceWriteOptions.OPERATION_OPT_KEY, "insert_overwrite_table").
> option("hoodie.insert.shuffle.parallelism", "4").
> option(HoodieWriteConfig.TABLE_NAME, "hoodie_test")
> .mode(SaveMode.Append).save(basePath)
>
> step4: query incrematal table
> spark.read.format("hudi").option(DataSourceReadOptions.QUERY_TYPE_OPT_KEY,
> DataSourceReadOptions.QUERY_TYPE_INCREMENTAL_OPT_VAL)
> .option(DataSourceReadOptions.BEGIN_INSTANTTIME_OPT_KEY, "0000")
> .option(DataSourceReadOptions.END_INSTANTTIME_OPT_KEY, currentCommits(0))
> .load(basePath).select("keyid").orderBy("keyid").show(100, false)
>
> result: the result contains old data
> +-----+
> |keyid|
> +-----+
> |0 |
> |0 |
> |1 |
> |1 |
> |2 |
> |2 |
> |3 |
> |3 |
> |4 |
> |4 |
> |5 |
> |5 |
> |6 |
> |6 |
> |7 |
> |7 |
> |8 |
> |8 |
> |9 |
> |9 |
> +-----+
>
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