jonvex commented on code in PR #12161:
URL: https://github.com/apache/hudi/pull/12161#discussion_r1857340990
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/TestStructuredStreaming.scala:
##########
@@ -498,15 +498,77 @@ class TestStructuredStreaming extends
HoodieSparkClientTestBase {
val inputDF1 = spark.read.json(spark.sparkContext.parallelize(records1, 2))
inputDF1.coalesce(1).write.mode(SaveMode.Append).json(sourcePath)
val opts = commonOpts + (DataSourceWriteOptions.TABLE_TYPE.key ->
HoodieTableType.MERGE_ON_READ.name()) +
(DataSourceWriteOptions.STREAMING_DISABLE_COMPACTION.key -> "true")
- streamingWrite(inputDF1.schema, sourcePath, destPath, opts, "000")
+ streamingWrite(inputDF1.schema, sourcePath, destPath, opts)
for (i <- 1 to 24) {
val id = String.format("%03d", new Integer(i))
val records = recordsToStrings(dataGen.generateUpdates(id,
10)).asScala.toList
val inputDF = spark.read.json(spark.sparkContext.parallelize(records, 2))
inputDF.coalesce(1).write.mode(SaveMode.Append).json(sourcePath)
- streamingWrite(inputDF.schema, sourcePath, destPath, opts, id)
+ streamingWrite(inputDF.schema, sourcePath, destPath, opts)
}
- val metaClient = HoodieTestUtils.createMetaClient(storage, destPath);
+ val metaClient = HoodieTestUtils.createMetaClient(storage, destPath)
assertTrue(metaClient.getActiveTimeline.getCommitAndReplaceTimeline.empty())
+ assertEquals(25, metaClient.getActiveTimeline.countInstants())
+ }
+
+ @ParameterizedTest
+ @CsvSource(Array(
+ "COPY_ON_WRITE,EVENT_TIME_ORDERING",
+ "MERGE_ON_READ,EVENT_TIME_ORDERING",
+ "COPY_ON_WRITE,COMMIT_TIME_ORDERING",
+ "MERGE_ON_READ,COMMIT_TIME_ORDERING",
+ "COPY_ON_WRITE,CUSTOM",
+ "MERGE_ON_READ,CUSTOM"))
+ def testStructuredStreamingWithMergeMode(tableType: String, mergerType:
String): Unit = {
+ val (sourcePath, destPath) = initStreamingSourceAndDestPath("source",
"dest")
+ // First chunk of data
+ val records1 = recordsToStrings(dataGen.generateInserts("000",
10)).asScala.toList
+ val inputDF1 = spark.read.json(spark.sparkContext.parallelize(records1, 2))
+ inputDF1.coalesce(1).write.mode(SaveMode.Append).json(sourcePath)
+ var opts = commonOpts ++ Map(DataSourceWriteOptions.OPERATION.key ->
UPSERT_OPERATION_OPT_VAL,
+ DataSourceWriteOptions.TABLE_TYPE.key() -> tableType,
+ DataSourceWriteOptions.RECORD_MERGE_MODE.key() -> mergerType,
+ HoodieStorageConfig.LOGFILE_DATA_BLOCK_FORMAT.key() -> "parquet",
+ DataSourceWriteOptions.PRECOMBINE_FIELD.key -> "weight")
+ if (mergerType == "CUSTOM") {
+ opts = opts ++ Map(DataSourceWriteOptions.RECORD_MERGE_STRATEGY_ID.key()
-> HoodieSparkDeleteRecordMerger.DELETE_MERGER_STRATEGY,
+ DataSourceWriteOptions.RECORD_MERGE_IMPL_CLASSES.key() ->
classOf[HoodieSparkDeleteRecordMerger].getName)
+ }
+ streamingWrite(inputDF1.schema, sourcePath, destPath, opts)
+
+
+ val records2 = recordsToStrings(dataGen.generateUniqueUpdates("001",
5)).asScala.toList
Review Comment:
I increased the size 100 inserts then 50 updates. So I think the chance of
not having any updates will be 1 / 2^50
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