koochiswathiTR opened a new issue, #6881:
URL: https://github.com/apache/hudi/issues/6881
We run spark streaming application, where we upsert data in hudi,
We have around 2000 partitions in our hudi dataset, we enabled metadata in
our hudi tables, after that we could see drastic change in processing time.
current processing time is 15 minutes. earlier processing time is 1 min or 1
min 30 sec.
We use inline compaction
with metadata enable which compaction would you prefer? Async or inline?
Wts the difference between Async and inline compaction.
Please suggest
Hudi props :
DataSourceWriteOptions.TABLE_TYPE.key() ->
DataSourceWriteOptions.MOR_TABLE_TYPE_OPT_VAL,
DataSourceWriteOptions.RECORDKEY_FIELD.key() -> "id",
DataSourceWriteOptions.PARTITIONPATH_FIELD.key() -> "col",
DataSourceWriteOptions.PRECOMBINE_FIELD.key() -> "optime",
DataSourceWriteOptions.HIVE_SYNC_ENABLED.key() -> "true",
DataSourceWriteOptions.HIVE_PARTITION_FIELDS.key() -> "col",
DataSourceWriteOptions.HIVE_PARTITION_EXTRACTOR_CLASS.key() ->
classOf[MultiPartKeysValueExtractor].getName,
DataSourceWriteOptions.HIVE_SYNC_MODE.key() -> "hms",
DataSourceWriteOptions.HIVE_USE_JDBC.key() -> "false",
HoodieCompactionConfig.INLINE_COMPACT_TRIGGER_STRATEGY.key() ->
CompactionTriggerStrategy.TIME_ELAPSED.name,
HoodieCompactionConfig.INLINE_COMPACT_TIME_DELTA_SECONDS.key() ->
String.valueOf(60 * 60),
HoodieCompactionConfig.CLEANER_COMMITS_RETAINED.key() -> "800",
HoodieCompactionConfig.ASYNC_CLEAN.key() -> "false",
HoodieCompactionConfig.INLINE_COMPACT.key() -> "true",
HoodieCompactionConfig.MIN_COMMITS_TO_KEEP.key() -> "801",
HoodieCompactionConfig.MAX_COMMITS_TO_KEEP.key() -> "825",
HoodieMetricsConfig.TURN_METRICS_ON.key() -> "true",
HoodieMetricsConfig.METRICS_REPORTER_TYPE_VALUE.key() ->
MetricsReporterType.DATADOG.name(),
HoodieMetricsDatadogConfig.API_SITE_VALUE.key() -> "US",
HoodieMetricsDatadogConfig.METRIC_PREFIX_VALUE.key() ->
"tacticalnovusingest.qa.hudi",
HoodieMetricsDatadogConfig.API_KEY_SUPPLIER.key() ->
"com.tr.indigo.tacticalnovusingest.utils.DatadogKeySupplier",
HoodieMetadataConfig.ENABLE.key() -> "false",
HoodieMetadataConfig.CLEANER_COMMITS_RETAINED.key() -> "800",
HoodieMetadataConfig.MIN_COMMITS_TO_KEEP.key() -> "801",
HoodieMetadataConfig.MAX_COMMITS_TO_KEEP.key() -> "825",
HoodieWriteConfig.ROLLBACK_USING_MARKERS_ENABLE.key() -> "false"
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**Describe the problem you faced**
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**To Reproduce**
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**Expected behavior** Processing time should be less than 2 mints,
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**Environment Description**
* Hudi version :
* Spark version : 3.12
* Hive version :
* Hadoop version :
* Storage (HDFS/S3/GCS..) : S3
* Running on Docker? (yes/no) :
**Additional context**
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**Stacktrace**
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