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[GitHub] [spark] vkorukanti opened a new pull request #33091: [WIP][SPARK-35896][SS] Include more granular metrics for stateful operators in StreamingQueryProgress
vkorukanti opened a new pull request #33091:
URL: https://github.com/apache/spark/pull/33091
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### What changes were proposed in this pull request?
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Currently the `StateOperatorProgress` in `StreamingQueryProgress` is missing few metrics.
### Why are the changes needed?
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The main motivation is find hotspots and have better visibility in the stateful operations. Detailed explanations are in [SPARK-35896](https://issues.apache.org/jira/browse/SPARK-35896).
### Does this PR introduce _any_ user-facing change?
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Yes. The `StateOperatorProgress` entries within `StreamingQueryProgress` now contain additional fields as listed in [SPARK-35896](https://issues.apache.org/jira/browse/SPARK-35896). Example `StreamingQueryProgress` output in JSON form.
Before:
```
{
"id" : "510be3cd-a955-4faf-8456-d97c78d39af5",
....
"durationMs" : {
"triggerExecution" : 2856,
....
},
"stateOperators" : [ {
"numRowsTotal" : 1,
"numRowsUpdated" : 1,
"numRowsDroppedByWatermark" : 0,
"customMetrics" : {
"loadedMapCacheHitCount" : 0,
"loadedMapCacheMissCount" : 0,
"stateOnCurrentVersionSizeBytes" : 392
}
}],
....
}
```
After:
```
{
"id" : "510be3cd-a955-4faf-8456-d97c78d39af5",
....
"durationMs" : {
"triggerExecution" : 2856,
....
},
"stateOperators" : [ {
"operatorName" : "dedupe", <-- new
"numRowsTotal" : 1,
"numRowsUpdated" : 1, <-- new
"allUpdatesTimeMs" : 56, <-- new
"numRowsRemoved" : 2, <-- new
"allRemovalsTimeMs" : 45, <-- new
"commitTimeMs" : 40, <-- new
"numRowsDroppedByWatermark" : 0,
"numShufflePartitions" : 2, <-- new
"numStores" : 2, <-- new
"customMetrics" : {
"loadedMapCacheHitCount" : 0,
"loadedMapCacheMissCount" : 0,
"stateOnCurrentVersionSizeBytes" : 392
}
}],
....
}
```
### How was this patch tested?
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Existing tests for regressions. Added new UTs. The tests need some cleanup and coverage for one of the new fields in `StateOperatorProgress`. Hence marked it as WIP. Will remove the WIP tag, once test updates are done.
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[GitHub] [spark] vkorukanti commented on a change in pull request #33091: [SPARK-35896][SS] Include more granular metrics for stateful operators in StreamingQueryProgress
Posted by GitBox <gi...@apache.org>.
vkorukanti commented on a change in pull request #33091:
URL: https://github.com/apache/spark/pull/33091#discussion_r661073820
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
##########
@@ -1122,6 +1106,43 @@ class FlatMapGroupsWithStateSuite extends StateStoreMetricsTest {
spark.createDataset(Seq(("a", 2), ("b", 1))).toDF)
}
+ test("SPARK-35896: metrics in StateOperatorProgress are output correctly") {
+ val inputData = MemoryStream[(String, Int)]
+ val result =
+ inputData.toDS
+ .select($"_1".as("key"), timestamp_seconds($"_2").as("eventTime"))
+ .withWatermark("eventTime", "10 seconds")
+ .as[(String, Long)]
+ .groupByKey(_._1)
+ .flatMapGroupsWithState(Update, EventTimeTimeout)(sampleTestFunction)
+
+ testStream(result, Update)(
+ StartStream(additionalConfs = Map(SQLConf.SHUFFLE_PARTITIONS.key -> "3")),
+
+ AddData(inputData, ("a", 11), ("a", 13), ("a", 15)),
+ // Max event time = 15. Timeout timestamp for "a" = 15 + 5 = 20. Watermark = 15 - 10 = 5.
+ CheckNewAnswer(("a", 15)), // Output = max event time of a
+ assertNumStateRows(
+ total = Seq(1), updated = Seq(1), droppedByWatermark = Seq(0), removed = Some(Seq(0))),
+
+ AddData(inputData, ("a", 4)), // Add data older than watermark for "a"
+ CheckNewAnswer(), // No output as data should get filtered by watermark
+ assertStateOperatorProgressMetric(
Review comment:
Got it. Renamed it to `numStateStoreInstances`.
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[GitHub] [spark] HeartSaVioR commented on a change in pull request #33091: [SPARK-35896][SS] Include more granular metrics for stateful operators in StreamingQueryProgress
Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on a change in pull request #33091:
URL: https://github.com/apache/spark/pull/33091#discussion_r660321229
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/FlatMapGroupsWithStateExec.scala
##########
@@ -127,12 +132,26 @@ case class FlatMapGroupsWithStateExec(
iter
}
+ val newDataProcessorIter =
+ CompletionIterator[InternalRow, Iterator[InternalRow]](
+ processor.processNewData(filteredIter), {
+ // Once the input is processed, mark the start time for timeout processing to measure
+ // it separately from the overall processing time.
+ timeoutProcessingStartTimeNs = System.nanoTime
+ })
+
+ val timeoutProcessorIter =
+ CompletionIterator[InternalRow, Iterator[InternalRow]](processor.processTimedOutState(), {
+ // Note: `timeoutLatencyMs` also includes the time the parent operator took for
+ // processing output returned through iterator.
+ timeoutLatencyMs += (System.nanoTime - timeoutProcessingStartTimeNs)
Review comment:
We need to convert to milliseconds here.
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
##########
@@ -1122,6 +1106,43 @@ class FlatMapGroupsWithStateSuite extends StateStoreMetricsTest {
spark.createDataset(Seq(("a", 2), ("b", 1))).toDF)
}
+ test("SPARK-35896: metrics in StateOperatorProgress are output correctly") {
+ val inputData = MemoryStream[(String, Int)]
+ val result =
+ inputData.toDS
+ .select($"_1".as("key"), timestamp_seconds($"_2").as("eventTime"))
+ .withWatermark("eventTime", "10 seconds")
+ .as[(String, Long)]
+ .groupByKey(_._1)
+ .flatMapGroupsWithState(Update, EventTimeTimeout)(sampleTestFunction)
+
+ testStream(result, Update)(
+ StartStream(additionalConfs = Map(SQLConf.SHUFFLE_PARTITIONS.key -> "3")),
+
+ AddData(inputData, ("a", 11), ("a", 13), ("a", 15)),
+ // Max event time = 15. Timeout timestamp for "a" = 15 + 5 = 20. Watermark = 15 - 10 = 5.
+ CheckNewAnswer(("a", 15)), // Output = max event time of a
+ assertNumStateRows(
+ total = Seq(1), updated = Seq(1), droppedByWatermark = Seq(0), removed = Some(Seq(0))),
+
+ AddData(inputData, ("a", 4)), // Add data older than watermark for "a"
+ CheckNewAnswer(), // No output as data should get filtered by watermark
+ assertStateOperatorProgressMetric(
Review comment:
The number of `numStateStores` is actually confusing. We have two different views of the number; someone may expect the right number as 1.
We may need to explain that the number represents "every" state store instances initialized in all tasks, otherwise people who think like above may think this as a bug.
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/StateStoreMetricsTest.scala
##########
@@ -58,9 +59,17 @@ trait StateStoreMetricsTest extends StreamTest {
val numRowsDroppedByWatermark = arraySum(allNumRowsDroppedByWatermarkSinceLastCheck,
numStateOperators)
+
Review comment:
nit: let's leave it as it was
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
##########
@@ -737,7 +761,7 @@ class FlatMapGroupsWithStateSuite extends StateStoreMetricsTest {
StartStream(),
AddData(inputData, "a", "b"), // should remove state for "a" and not return anything for a
CheckNewAnswer(("b", "2")),
- assertNumStateRows(total = 1, updated = 2),
+ assertNumStateRows(total = 1, updated = 1),
Review comment:
Could we please retain checking the 1 here? I guess it's related to "removal". Below changes as well.
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[GitHub] [spark] vkorukanti commented on a change in pull request #33091: [SPARK-35896][SS] Include more granular metrics for stateful operators in StreamingQueryProgress
Posted by GitBox <gi...@apache.org>.
vkorukanti commented on a change in pull request #33091:
URL: https://github.com/apache/spark/pull/33091#discussion_r660639490
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
##########
@@ -1122,6 +1106,43 @@ class FlatMapGroupsWithStateSuite extends StateStoreMetricsTest {
spark.createDataset(Seq(("a", 2), ("b", 1))).toDF)
}
+ test("SPARK-35896: metrics in StateOperatorProgress are output correctly") {
+ val inputData = MemoryStream[(String, Int)]
+ val result =
+ inputData.toDS
+ .select($"_1".as("key"), timestamp_seconds($"_2").as("eventTime"))
+ .withWatermark("eventTime", "10 seconds")
+ .as[(String, Long)]
+ .groupByKey(_._1)
+ .flatMapGroupsWithState(Update, EventTimeTimeout)(sampleTestFunction)
+
+ testStream(result, Update)(
+ StartStream(additionalConfs = Map(SQLConf.SHUFFLE_PARTITIONS.key -> "3")),
+
+ AddData(inputData, ("a", 11), ("a", 13), ("a", 15)),
+ // Max event time = 15. Timeout timestamp for "a" = 15 + 5 = 20. Watermark = 15 - 10 = 5.
+ CheckNewAnswer(("a", 15)), // Output = max event time of a
+ assertNumStateRows(
+ total = Seq(1), updated = Seq(1), droppedByWatermark = Seq(0), removed = Some(Seq(0))),
+
+ AddData(inputData, ("a", 4)), // Add data older than watermark for "a"
+ CheckNewAnswer(), // No output as data should get filtered by watermark
+ assertStateOperatorProgressMetric(
Review comment:
how about `numStateStoreInstances`? One other thing is we could remove this entirely as the this number can be derived using `numShufflePartitions` and the `operatorName` (need to know the implementation details).
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retest this, please
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GA passed. Thanks! Merging to master.
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[GitHub] [spark] HeartSaVioR commented on a change in pull request #33091: [SPARK-35896][SS] Include more granular metrics for stateful operators in StreamingQueryProgress
Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on a change in pull request #33091:
URL: https://github.com/apache/spark/pull/33091#discussion_r660321229
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/FlatMapGroupsWithStateExec.scala
##########
@@ -127,12 +132,26 @@ case class FlatMapGroupsWithStateExec(
iter
}
+ val newDataProcessorIter =
+ CompletionIterator[InternalRow, Iterator[InternalRow]](
+ processor.processNewData(filteredIter), {
+ // Once the input is processed, mark the start time for timeout processing to measure
+ // it separately from the overall processing time.
+ timeoutProcessingStartTimeNs = System.nanoTime
+ })
+
+ val timeoutProcessorIter =
+ CompletionIterator[InternalRow, Iterator[InternalRow]](processor.processTimedOutState(), {
+ // Note: `timeoutLatencyMs` also includes the time the parent operator took for
+ // processing output returned through iterator.
+ timeoutLatencyMs += (System.nanoTime - timeoutProcessingStartTimeNs)
Review comment:
We need to convert to milliseconds here.
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
##########
@@ -1122,6 +1106,43 @@ class FlatMapGroupsWithStateSuite extends StateStoreMetricsTest {
spark.createDataset(Seq(("a", 2), ("b", 1))).toDF)
}
+ test("SPARK-35896: metrics in StateOperatorProgress are output correctly") {
+ val inputData = MemoryStream[(String, Int)]
+ val result =
+ inputData.toDS
+ .select($"_1".as("key"), timestamp_seconds($"_2").as("eventTime"))
+ .withWatermark("eventTime", "10 seconds")
+ .as[(String, Long)]
+ .groupByKey(_._1)
+ .flatMapGroupsWithState(Update, EventTimeTimeout)(sampleTestFunction)
+
+ testStream(result, Update)(
+ StartStream(additionalConfs = Map(SQLConf.SHUFFLE_PARTITIONS.key -> "3")),
+
+ AddData(inputData, ("a", 11), ("a", 13), ("a", 15)),
+ // Max event time = 15. Timeout timestamp for "a" = 15 + 5 = 20. Watermark = 15 - 10 = 5.
+ CheckNewAnswer(("a", 15)), // Output = max event time of a
+ assertNumStateRows(
+ total = Seq(1), updated = Seq(1), droppedByWatermark = Seq(0), removed = Some(Seq(0))),
+
+ AddData(inputData, ("a", 4)), // Add data older than watermark for "a"
+ CheckNewAnswer(), // No output as data should get filtered by watermark
+ assertStateOperatorProgressMetric(
Review comment:
The number of `numStateStores` is actually confusing. We have two different views of the number; someone may expect the right number as 1.
We may need to explain that the number represents "every" state store instances initialized in all tasks, otherwise people who think like above may think this as a bug.
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/StateStoreMetricsTest.scala
##########
@@ -58,9 +59,17 @@ trait StateStoreMetricsTest extends StreamTest {
val numRowsDroppedByWatermark = arraySum(allNumRowsDroppedByWatermarkSinceLastCheck,
numStateOperators)
+
Review comment:
nit: let's leave it as it was
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
##########
@@ -737,7 +761,7 @@ class FlatMapGroupsWithStateSuite extends StateStoreMetricsTest {
StartStream(),
AddData(inputData, "a", "b"), // should remove state for "a" and not return anything for a
CheckNewAnswer(("b", "2")),
- assertNumStateRows(total = 1, updated = 2),
+ assertNumStateRows(total = 1, updated = 1),
Review comment:
Could we please retain checking the 1 here? I guess it's related to "removal". Below changes as well.
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Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on a change in pull request #33091:
URL: https://github.com/apache/spark/pull/33091#discussion_r661057587
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
##########
@@ -1122,6 +1106,43 @@ class FlatMapGroupsWithStateSuite extends StateStoreMetricsTest {
spark.createDataset(Seq(("a", 2), ("b", 1))).toDF)
}
+ test("SPARK-35896: metrics in StateOperatorProgress are output correctly") {
+ val inputData = MemoryStream[(String, Int)]
+ val result =
+ inputData.toDS
+ .select($"_1".as("key"), timestamp_seconds($"_2").as("eventTime"))
+ .withWatermark("eventTime", "10 seconds")
+ .as[(String, Long)]
+ .groupByKey(_._1)
+ .flatMapGroupsWithState(Update, EventTimeTimeout)(sampleTestFunction)
+
+ testStream(result, Update)(
+ StartStream(additionalConfs = Map(SQLConf.SHUFFLE_PARTITIONS.key -> "3")),
+
+ AddData(inputData, ("a", 11), ("a", 13), ("a", 15)),
+ // Max event time = 15. Timeout timestamp for "a" = 15 + 5 = 20. Watermark = 15 - 10 = 5.
+ CheckNewAnswer(("a", 15)), // Output = max event time of a
+ assertNumStateRows(
+ total = Seq(1), updated = Seq(1), droppedByWatermark = Seq(0), removed = Some(Seq(0))),
+
+ AddData(inputData, ("a", 4)), // Add data older than watermark for "a"
+ CheckNewAnswer(), // No output as data should get filtered by watermark
+ assertStateOperatorProgressMetric(
Review comment:
numStateStoreInstances seems OK to me. I'd rather not expect every end users would know how many kinds of state stores each stateful operator uses. It'd be ideal if we have a kind of state operator metrics which are not collected from each task, but let's put aside for now.
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[GitHub] [spark] dongjoon-hyun commented on a change in pull request #33091: [SPARK-35896][SS] Include more granular metrics for stateful operators in StreamingQueryProgress
Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on a change in pull request #33091:
URL: https://github.com/apache/spark/pull/33091#discussion_r663305160
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/streaming/progress.scala
##########
@@ -41,10 +41,17 @@ import org.apache.spark.sql.streaming.SinkProgress.DEFAULT_NUM_OUTPUT_ROWS
*/
@Evolving
class StateOperatorProgress private[sql](
+ val operatorName: String,
val numRowsTotal: Long,
val numRowsUpdated: Long,
+ val allUpdatesTimeMs: Long,
+ val numRowsRemoved: Long,
+ val allRemovalsTimeMs: Long,
+ val commitTimeMs: Long,
val memoryUsedBytes: Long,
val numRowsDroppedByWatermark: Long,
+ val numShufflePartitions: Long,
+ val numStateStoreInstances: Long,
Review comment:
This is detected as a binary incompatibility. It will be okay because this is Evolving.
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