yihua commented on code in PR #9273:
URL: https://github.com/apache/hudi/pull/9273#discussion_r1272478660
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/TestCOWDataSource.scala:
##########
@@ -941,6 +942,70 @@ class TestCOWDataSource extends HoodieSparkClientTestBase
with ScalaAssertionSup
}
}
+ @ParameterizedTest
+ @EnumSource(value = classOf[HoodieRecordType], names = Array("AVRO",
"SPARK"))
+ def testSparkPartitionByWithCustomKeyGenerator(recordType:
HoodieRecordType): Unit = {
+ val (writeOpts, readOpts) =
getWriterReaderOptsLessPartitionPath(recordType)
+ // Specify fieldType as TIMESTAMP of type EPOCHMILLISECONDS and output
date format as yyyy/MM/dd
+ var writer = getDataFrameWriter(classOf[CustomKeyGenerator].getName,
writeOpts)
+ writer.partitionBy("current_ts:TIMESTAMP")
+ .option(TIMESTAMP_TYPE_FIELD.key, "EPOCHMILLISECONDS")
+ .option(TIMESTAMP_OUTPUT_DATE_FORMAT.key, "yyyy/MM/dd")
+ .mode(SaveMode.Overwrite)
+ .save(basePath)
+ var recordsReadDF = spark.read.format("org.apache.hudi")
+ .options(readOpts)
+ .load(basePath)
+ val udf_date_format = udf((data: Long) => new
DateTime(data).toString(DateTimeFormat.forPattern("yyyy/MM/dd")))
+
+ assertEquals(0L, recordsReadDF.filter(col("_hoodie_partition_path") =!=
udf_date_format(col("current_ts"))).count())
+
+ // Mixed fieldType with TIMESTAMP of type EPOCHMILLISECONDS and output
date format as yyyy/MM/dd
+ writer = getDataFrameWriter(classOf[CustomKeyGenerator].getName, writeOpts)
+ writer.partitionBy("driver", "rider:SIMPLE", "current_ts:TIMESTAMP")
+ .option(TIMESTAMP_TYPE_FIELD.key, "EPOCHMILLISECONDS")
+ .option(TIMESTAMP_OUTPUT_DATE_FORMAT.key, "yyyy/MM/dd")
+ .mode(SaveMode.Overwrite)
+ .save(basePath)
+ recordsReadDF = spark.read.format("org.apache.hudi")
+ .options(readOpts)
+ .load(basePath)
+ assertTrue(recordsReadDF.filter(col("_hoodie_partition_path") =!=
+ concat(col("driver"), lit("/"), col("rider"), lit("/"),
udf_date_format(col("current_ts")))).count() == 0)
+ }
+
+ @Test
+ def testPartitionPruningForTimestampBasedKeyGenerator(): Unit = {
+ val (writeOpts, readOpts) =
getWriterReaderOptsLessPartitionPath(HoodieRecordType.AVRO, enableFileIndex =
true)
+ val writer =
getDataFrameWriter(classOf[TimestampBasedKeyGenerator].getName, writeOpts)
+ writer.partitionBy("current_ts")
+ .option(TIMESTAMP_TYPE_FIELD.key, "EPOCHMILLISECONDS")
+ .option(TIMESTAMP_OUTPUT_DATE_FORMAT.key, "yyyy/MM/dd")
+ .mode(SaveMode.Overwrite)
+ .save(basePath)
+
+ val snapshotQueryRes = spark.read.format("hudi")
+ .options(readOpts)
+ .load(basePath)
+ .where("current_ts > '1970/01/16'")
+
assertTrue(checkPartitionFilters(snapshotQueryRes.queryExecution.executedPlan.toString,
"current_ts.* > 1970/01/16"))
Review Comment:
+1
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/HoodieFileIndex.scala:
##########
@@ -342,6 +342,20 @@ object HoodieFileIndex extends Logging {
if (listingModeOverride != null) {
properties.setProperty(DataSourceReadOptions.FILE_INDEX_LISTING_MODE_OVERRIDE.key,
listingModeOverride)
}
+ val tableConfig = metaClient.getTableConfig
+ val partitionColumns = tableConfig.getPartitionFields
+ if (partitionColumns.isPresent) {
+ val keyGeneratorClassName = tableConfig.getKeyGeneratorClassName
+ // NOTE: A custom key generator with multiple fields could have
non-encoded slashes in the partition columns'
+ // value. We might not be able to properly parse partition-values
from the listed partition-paths. Fallback
+ // to eager listing in this case.
+ val isCustomKeyGenerator =
(classOf[CustomKeyGenerator].getName.equalsIgnoreCase(keyGeneratorClassName)
+ ||
classOf[CustomAvroKeyGenerator].getName.equalsIgnoreCase(keyGeneratorClassName))
+ val hasMultiplePartitionFields = partitionColumns.get().length > 1
+ if (hasMultiplePartitionFields && isCustomKeyGenerator) {
+
properties.setProperty(DataSourceReadOptions.FILE_INDEX_LISTING_MODE_OVERRIDE.key,
DataSourceReadOptions.FILE_INDEX_LISTING_MODE_EAGER)
+ }
+ }
Review Comment:
nit: only execute this part if `listingModeOverride` is lazy?
##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/TestCOWDataSource.scala:
##########
@@ -941,6 +942,70 @@ class TestCOWDataSource extends HoodieSparkClientTestBase
with ScalaAssertionSup
}
}
+ @ParameterizedTest
+ @EnumSource(value = classOf[HoodieRecordType], names = Array("AVRO",
"SPARK"))
+ def testSparkPartitionByWithCustomKeyGenerator(recordType:
HoodieRecordType): Unit = {
+ val (writeOpts, readOpts) =
getWriterReaderOptsLessPartitionPath(recordType)
+ // Specify fieldType as TIMESTAMP of type EPOCHMILLISECONDS and output
date format as yyyy/MM/dd
+ var writer = getDataFrameWriter(classOf[CustomKeyGenerator].getName,
writeOpts)
+ writer.partitionBy("current_ts:TIMESTAMP")
+ .option(TIMESTAMP_TYPE_FIELD.key, "EPOCHMILLISECONDS")
+ .option(TIMESTAMP_OUTPUT_DATE_FORMAT.key, "yyyy/MM/dd")
+ .mode(SaveMode.Overwrite)
+ .save(basePath)
+ var recordsReadDF = spark.read.format("org.apache.hudi")
+ .options(readOpts)
+ .load(basePath)
+ val udf_date_format = udf((data: Long) => new
DateTime(data).toString(DateTimeFormat.forPattern("yyyy/MM/dd")))
+
+ assertEquals(0L, recordsReadDF.filter(col("_hoodie_partition_path") =!=
udf_date_format(col("current_ts"))).count())
+
+ // Mixed fieldType with TIMESTAMP of type EPOCHMILLISECONDS and output
date format as yyyy/MM/dd
+ writer = getDataFrameWriter(classOf[CustomKeyGenerator].getName, writeOpts)
+ writer.partitionBy("driver", "rider:SIMPLE", "current_ts:TIMESTAMP")
+ .option(TIMESTAMP_TYPE_FIELD.key, "EPOCHMILLISECONDS")
+ .option(TIMESTAMP_OUTPUT_DATE_FORMAT.key, "yyyy/MM/dd")
+ .mode(SaveMode.Overwrite)
+ .save(basePath)
+ recordsReadDF = spark.read.format("org.apache.hudi")
Review Comment:
nit: use `.format("hudi")`?
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