[GitHub] [spark] HyukjinKwon commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
HyukjinKwon commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r673587148
##
File path: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
##
@@ -1947,6 +1947,31 @@ class Dataset[T] private[sql](
CollectMetrics(name, (expr +: exprs).map(_.named), logicalPlan)
}
+ /**
+ * Observe (named) metrics through an `org.apache.spark.sql.Observation`
instance.
+ * This is equivalent to calling `observe(String, Column, Column*)` but does
not require
+ * adding `org.apache.spark.sql.util.QueryExecutionListener` to the spark
session.
+ * This method does not support streaming datasets.
+ *
+ * A user can retrieve the metrics by accessing
`org.apache.spark.sql.Observation.get`.
+ *
+ * {{{
+ * // Observe row count (rows) and highest id (maxid) in the Dataset while
writing it
+ * val observation = Observation("my_metrics")
+ * val observed_ds = ds.observe(observation, count(lit(1)).as("rows"),
max($"id").as("maxid"))
+ * observed_ds.write.parquet("ds.parquet")
+ * val metrics = observation.get
+ * }}}
+ *
+ * @throws IllegalArgumentException If this is a streaming Dataset
(this.isStreaming == true)
+ *
+ * @group typedrel
+ * @since 3.3.0
+ */
+ def observe(observation: Observation, expr: Column, exprs: Column*):
Dataset[T] = {
Review comment:
That's fine. Let's don't add it for now
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
HyukjinKwon commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r673112471
##
File path: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
##
@@ -1947,6 +1947,31 @@ class Dataset[T] private[sql](
CollectMetrics(name, (expr +: exprs).map(_.named), logicalPlan)
}
+ /**
+ * Observe (named) metrics through an `org.apache.spark.sql.Observation`
instance.
+ * This is equivalent to calling `observe(String, Column, Column*)` but does
not require
+ * adding `org.apache.spark.sql.util.QueryExecutionListener` to the spark
session.
+ * This method does not support streaming datasets.
+ *
+ * A user can retrieve the metrics by accessing
`org.apache.spark.sql.Observation.get`.
+ *
+ * {{{
+ * // Observe row count (rows) and highest id (maxid) in the Dataset while
writing it
+ * val observation = Observation("my_metrics")
+ * val observed_ds = ds.observe(observation, count(lit(1)).as("rows"),
max($"id").as("maxid"))
+ * observed_ds.write.parquet("ds.parquet")
+ * val metrics = observation.get
+ * }}}
+ *
+ * @throws IllegalArgumentException If this is a streaming Dataset
(this.isStreaming == true)
+ *
+ * @group typedrel
+ * @since 3.3.0
+ */
+ def observe(observation: Observation, expr: Column, exprs: Column*):
Dataset[T] = {
Review comment:
oh yeah!
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
HyukjinKwon commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r672721125
##
File path: sql/core/src/main/scala/org/apache/spark/sql/Observation.scala
##
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+
+import java.util.UUID
+
+import org.apache.spark.sql.execution.QueryExecution
+import org.apache.spark.sql.util.QueryExecutionListener
+
+
+/**
+ * Helper class to simplify usage of `Dataset.observe(String, Column,
Column*)`:
+ *
+ * {{{
+ * // Observe row count (rows) and highest id (maxid) in the Dataset while
writing it
+ * val observation = Observation("my metrics")
+ * val observed_ds = ds.observe(observation, count(lit(1)).as("rows"),
max($"id").as("maxid"))
+ * observed_ds.write.parquet("ds.parquet")
+ * val metrics = observation.get
+ * }}}
+ *
+ * This collects the metrics while the first action is executed on the
observed dataset. Subsequent
+ * actions do not modify the metrics returned by [[get]]. Retrieval of the
metric via [[get]]
+ * blocks until the first action has finished and metrics become available.
+ *
+ * This class does not support streaming datasets.
+ *
+ * @param name name of the metric
+ * @since 3.3.0
+ */
+class Observation(name: String) {
+
+ private val listener: ObservationListener = ObservationListener(this)
+
+ @volatile private var sparkSession: Option[SparkSession] = None
+
+ @volatile private var row: Option[Row] = None
+
+ /**
+ * Attach this observation to the given [[Dataset]] to observe aggregation
expressions.
+ *
+ * @param ds dataset
+ * @param expr first aggregation expression
+ * @param exprs more aggregation expressions
+ * @tparam T dataset type
+ * @return observed dataset
+ * @throws IllegalArgumentException If this is a streaming Dataset
(ds.isStreaming == true)
+ */
+ private[spark] def on[T](ds: Dataset[T], expr: Column, exprs: Column*):
Dataset[T] = {
+if (ds.isStreaming) {
+ throw new IllegalArgumentException("Observation does not support
streaming Datasets")
+}
+register(ds.sparkSession)
+ds.observe(name, expr, exprs: _*)
+ }
+
+ /**
+ * Get the observed metrics. This waits for the observed dataset to finish
its first action.
+ * Only the result of the first action is available. Subsequent actions do
not modify the result.
+ *
+ * @return the observed metrics as a [[Row]]
+ * @throws InterruptedException interrupted while waiting
+ */
+ @throws[InterruptedException]
+ def get: Row = {
+synchronized {
+ // we need to loop as wait might return without us calling notify
+ //
https://en.wikipedia.org/w/index.php?title=Spurious_wakeup&oldid=992601610
+ while (this.row.isEmpty) {
+wait()
+ }
+}
+
+this.row.get
+ }
+
+ private def register(sparkSession: SparkSession): Unit = {
+// makes this class thread-safe:
+// only the first thread entering this block can set sparkSession
+// all other threads will see the exception, as it is only allowed to do
this once
+synchronized {
+ if (this.sparkSession.isDefined) {
+throw new IllegalArgumentException("An Observation can be used with a
Dataset only once")
+ }
+ this.sparkSession = Some(sparkSession)
+}
+
+sparkSession.listenerManager.register(this.listener)
+ }
+
+ private def unregister(): Unit = {
+this.sparkSession.foreach(_.listenerManager.unregister(this.listener))
+ }
+
+ private[spark] def onFinish(qe: QueryExecution): Unit = {
+synchronized {
+ if (this.row.isEmpty) {
+this.row = qe.observedMetrics.get(name)
+if (this.row.isDefined) {
+ notifyAll()
+ unregister()
+}
+ }
+}
+ }
+
+}
+
+private[sql] case class ObservationListener(observation: Observation)
+ extends QueryExecutionListener {
+
+ override def onSuccess(funcName: String, qe: QueryExecution, durationNs:
Long): Unit =
+observation.onFinish(qe)
+
+ override def onFailure(funcName: String, qe: QueryExecution, exception:
Exception): Unit =
+observation.onFinish(qe)
+
+}
+
+/**
+ * (Scala-specific) Create a named or anonym
[GitHub] [spark] HyukjinKwon commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
HyukjinKwon commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r672980755
##
File path:
sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java
##
@@ -523,4 +523,55 @@ public void testUDF() {
.map(row -> row.get(0).toString() +
row.getString(1)).toArray(String[]::new);
Assert.assertArrayEquals(expected, result);
}
+
+ /**
+ * Tests the Java API of Observation and Dataset.observe(Observation,
Column, Column*).
+ */
+ @Test
+ public void testObservation() {
+Observation namedObservation = new Observation("named");
+Observation unnamedObservation = new Observation();
+
+Dataset df = spark
+.range(100)
+.observe(
+namedObservation,
+min(col("id")).as("min_val"),
+
scala.collection.JavaConverters.asScalaBuffer(Arrays.asList(
+max(col("id")).as("max_val"),
+sum(col("id")).as("sum_val"),
+count(when(pmod(col("id"), lit(2)).$eq$eq$eq(0),
1)).as("num_even")
+))
+)
+.observe(
+unnamedObservation,
+avg(col("id")).cast("int").as("avg_val"),
+
scala.collection.JavaConverters.asScalaBuffer(Arrays.asList())
+);
+
+df.collect();
+Row namedMetrics = null;
+Row unnamedMetrics = null;
+
+try {
+ // we can get the result multiple times
+ namedMetrics = namedObservation.get();
+ unnamedMetrics = unnamedObservation.get();
+} catch (InterruptedException e) {
+ Assert.fail();
+}
+Assert.assertEquals(Arrays.asList(0L, 99L, 4950L, 50L),
scala.collection.JavaConverters.seqAsJavaList(namedMetrics.toSeq()));
Review comment:
I think the current way is fine.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
HyukjinKwon commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r672721125
##
File path: sql/core/src/main/scala/org/apache/spark/sql/Observation.scala
##
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+
+import java.util.UUID
+
+import org.apache.spark.sql.execution.QueryExecution
+import org.apache.spark.sql.util.QueryExecutionListener
+
+
+/**
+ * Helper class to simplify usage of `Dataset.observe(String, Column,
Column*)`:
+ *
+ * {{{
+ * // Observe row count (rows) and highest id (maxid) in the Dataset while
writing it
+ * val observation = Observation("my metrics")
+ * val observed_ds = ds.observe(observation, count(lit(1)).as("rows"),
max($"id").as("maxid"))
+ * observed_ds.write.parquet("ds.parquet")
+ * val metrics = observation.get
+ * }}}
+ *
+ * This collects the metrics while the first action is executed on the
observed dataset. Subsequent
+ * actions do not modify the metrics returned by [[get]]. Retrieval of the
metric via [[get]]
+ * blocks until the first action has finished and metrics become available.
+ *
+ * This class does not support streaming datasets.
+ *
+ * @param name name of the metric
+ * @since 3.3.0
+ */
+class Observation(name: String) {
+
+ private val listener: ObservationListener = ObservationListener(this)
+
+ @volatile private var sparkSession: Option[SparkSession] = None
+
+ @volatile private var row: Option[Row] = None
+
+ /**
+ * Attach this observation to the given [[Dataset]] to observe aggregation
expressions.
+ *
+ * @param ds dataset
+ * @param expr first aggregation expression
+ * @param exprs more aggregation expressions
+ * @tparam T dataset type
+ * @return observed dataset
+ * @throws IllegalArgumentException If this is a streaming Dataset
(ds.isStreaming == true)
+ */
+ private[spark] def on[T](ds: Dataset[T], expr: Column, exprs: Column*):
Dataset[T] = {
+if (ds.isStreaming) {
+ throw new IllegalArgumentException("Observation does not support
streaming Datasets")
+}
+register(ds.sparkSession)
+ds.observe(name, expr, exprs: _*)
+ }
+
+ /**
+ * Get the observed metrics. This waits for the observed dataset to finish
its first action.
+ * Only the result of the first action is available. Subsequent actions do
not modify the result.
+ *
+ * @return the observed metrics as a [[Row]]
+ * @throws InterruptedException interrupted while waiting
+ */
+ @throws[InterruptedException]
+ def get: Row = {
+synchronized {
+ // we need to loop as wait might return without us calling notify
+ //
https://en.wikipedia.org/w/index.php?title=Spurious_wakeup&oldid=992601610
+ while (this.row.isEmpty) {
+wait()
+ }
+}
+
+this.row.get
+ }
+
+ private def register(sparkSession: SparkSession): Unit = {
+// makes this class thread-safe:
+// only the first thread entering this block can set sparkSession
+// all other threads will see the exception, as it is only allowed to do
this once
+synchronized {
+ if (this.sparkSession.isDefined) {
+throw new IllegalArgumentException("An Observation can be used with a
Dataset only once")
+ }
+ this.sparkSession = Some(sparkSession)
+}
+
+sparkSession.listenerManager.register(this.listener)
+ }
+
+ private def unregister(): Unit = {
+this.sparkSession.foreach(_.listenerManager.unregister(this.listener))
+ }
+
+ private[spark] def onFinish(qe: QueryExecution): Unit = {
+synchronized {
+ if (this.row.isEmpty) {
+this.row = qe.observedMetrics.get(name)
+if (this.row.isDefined) {
+ notifyAll()
+ unregister()
+}
+ }
+}
+ }
+
+}
+
+private[sql] case class ObservationListener(observation: Observation)
+ extends QueryExecutionListener {
+
+ override def onSuccess(funcName: String, qe: QueryExecution, durationNs:
Long): Unit =
+observation.onFinish(qe)
+
+ override def onFailure(funcName: String, qe: QueryExecution, exception:
Exception): Unit =
+observation.onFinish(qe)
+
+}
+
+/**
+ * (Scala-specific) Create a named or anonym
[GitHub] [spark] HyukjinKwon commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
HyukjinKwon commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r672937934
##
File path:
sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java
##
@@ -523,4 +523,55 @@ public void testUDF() {
.map(row -> row.get(0).toString() +
row.getString(1)).toArray(String[]::new);
Assert.assertArrayEquals(expected, result);
}
+
+ /**
+ * Tests the Java API of Observation and Dataset.observe(Observation,
Column, Column*).
+ */
+ @Test
+ public void testObservation() {
+Observation namedObservation = new Observation("named");
+Observation unnamedObservation = new Observation();
+
+Dataset df = spark
+.range(100)
Review comment:
Actually we should keep it with 2 space indentation here same as Scala
side.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
HyukjinKwon commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r672800804
##
File path: sql/core/src/main/scala/org/apache/spark/sql/Observation.scala
##
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+
+import java.util.UUID
+
+import org.apache.spark.sql.execution.QueryExecution
+import org.apache.spark.sql.util.QueryExecutionListener
+
+
+/**
+ * Helper class to simplify usage of `Dataset.observe(String, Column,
Column*)`:
+ *
+ * {{{
+ * // Observe row count (rows) and highest id (maxid) in the Dataset while
writing it
+ * val observation = Observation("my metrics")
+ * val observed_ds = ds.observe(observation, count(lit(1)).as("rows"),
max($"id").as("maxid"))
+ * observed_ds.write.parquet("ds.parquet")
+ * val metrics = observation.get
+ * }}}
+ *
+ * This collects the metrics while the first action is executed on the
observed dataset. Subsequent
+ * actions do not modify the metrics returned by [[get]]. Retrieval of the
metric via [[get]]
+ * blocks until the first action has finished and metrics become available.
+ *
+ * This class does not support streaming datasets.
+ *
+ * @param name name of the metric
+ * @since 3.3.0
+ */
+class Observation(name: String) {
+
+ private val listener: ObservationListener = ObservationListener(this)
+
+ @volatile private var sparkSession: Option[SparkSession] = None
+
+ @volatile private var row: Option[Row] = None
+
+ /**
+ * Attach this observation to the given [[Dataset]] to observe aggregation
expressions.
+ *
+ * @param ds dataset
+ * @param expr first aggregation expression
+ * @param exprs more aggregation expressions
+ * @tparam T dataset type
+ * @return observed dataset
+ * @throws IllegalArgumentException If this is a streaming Dataset
(ds.isStreaming == true)
+ */
+ private[spark] def on[T](ds: Dataset[T], expr: Column, exprs: Column*):
Dataset[T] = {
+if (ds.isStreaming) {
+ throw new IllegalArgumentException("Observation does not support
streaming Datasets")
+}
+register(ds.sparkSession)
+ds.observe(name, expr, exprs: _*)
+ }
+
+ /**
+ * Get the observed metrics. This waits for the observed dataset to finish
its first action.
+ * Only the result of the first action is available. Subsequent actions do
not modify the result.
+ *
+ * @return the observed metrics as a [[Row]]
+ * @throws InterruptedException interrupted while waiting
+ */
+ @throws[InterruptedException]
+ def get: Row = {
+synchronized {
+ // we need to loop as wait might return without us calling notify
+ //
https://en.wikipedia.org/w/index.php?title=Spurious_wakeup&oldid=992601610
+ while (this.row.isEmpty) {
+wait()
+ }
+}
+
+this.row.get
+ }
+
+ private def register(sparkSession: SparkSession): Unit = {
+// makes this class thread-safe:
+// only the first thread entering this block can set sparkSession
+// all other threads will see the exception, as it is only allowed to do
this once
+synchronized {
+ if (this.sparkSession.isDefined) {
+throw new IllegalArgumentException("An Observation can be used with a
Dataset only once")
+ }
+ this.sparkSession = Some(sparkSession)
+}
+
+sparkSession.listenerManager.register(this.listener)
+ }
+
+ private def unregister(): Unit = {
+this.sparkSession.foreach(_.listenerManager.unregister(this.listener))
+ }
+
+ private[spark] def onFinish(qe: QueryExecution): Unit = {
+synchronized {
+ if (this.row.isEmpty) {
+this.row = qe.observedMetrics.get(name)
+if (this.row.isDefined) {
+ notifyAll()
+ unregister()
+}
+ }
+}
+ }
+
+}
+
+private[sql] case class ObservationListener(observation: Observation)
+ extends QueryExecutionListener {
+
+ override def onSuccess(funcName: String, qe: QueryExecution, durationNs:
Long): Unit =
+observation.onFinish(qe)
+
+ override def onFailure(funcName: String, qe: QueryExecution, exception:
Exception): Unit =
+observation.onFinish(qe)
+
+}
+
+/**
+ * (Scala-specific) Create a named or anonym
[GitHub] [spark] HyukjinKwon commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
HyukjinKwon commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r672800470
##
File path: sql/core/src/main/scala/org/apache/spark/sql/Observation.scala
##
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+
+import java.util.UUID
+
+import org.apache.spark.sql.execution.QueryExecution
+import org.apache.spark.sql.util.QueryExecutionListener
+
+
+/**
+ * Helper class to simplify usage of `Dataset.observe(String, Column,
Column*)`:
+ *
+ * {{{
+ * // Observe row count (rows) and highest id (maxid) in the Dataset while
writing it
+ * val observation = Observation("my metrics")
+ * val observed_ds = ds.observe(observation, count(lit(1)).as("rows"),
max($"id").as("maxid"))
+ * observed_ds.write.parquet("ds.parquet")
+ * val metrics = observation.get
+ * }}}
+ *
+ * This collects the metrics while the first action is executed on the
observed dataset. Subsequent
+ * actions do not modify the metrics returned by [[get]]. Retrieval of the
metric via [[get]]
+ * blocks until the first action has finished and metrics become available.
+ *
+ * This class does not support streaming datasets.
+ *
+ * @param name name of the metric
+ * @since 3.3.0
+ */
+class Observation(name: String) {
+
+ private val listener: ObservationListener = ObservationListener(this)
+
+ @volatile private var sparkSession: Option[SparkSession] = None
+
+ @volatile private var row: Option[Row] = None
+
+ /**
+ * Attach this observation to the given [[Dataset]] to observe aggregation
expressions.
+ *
+ * @param ds dataset
+ * @param expr first aggregation expression
+ * @param exprs more aggregation expressions
+ * @tparam T dataset type
+ * @return observed dataset
+ * @throws IllegalArgumentException If this is a streaming Dataset
(ds.isStreaming == true)
+ */
+ private[spark] def on[T](ds: Dataset[T], expr: Column, exprs: Column*):
Dataset[T] = {
+if (ds.isStreaming) {
+ throw new IllegalArgumentException("Observation does not support
streaming Datasets")
+}
+register(ds.sparkSession)
+ds.observe(name, expr, exprs: _*)
+ }
+
+ /**
+ * Get the observed metrics. This waits for the observed dataset to finish
its first action.
+ * Only the result of the first action is available. Subsequent actions do
not modify the result.
+ *
+ * @return the observed metrics as a [[Row]]
+ * @throws InterruptedException interrupted while waiting
+ */
+ @throws[InterruptedException]
+ def get: Row = {
+synchronized {
+ // we need to loop as wait might return without us calling notify
+ //
https://en.wikipedia.org/w/index.php?title=Spurious_wakeup&oldid=992601610
+ while (this.row.isEmpty) {
+wait()
+ }
+}
+
+this.row.get
+ }
+
+ private def register(sparkSession: SparkSession): Unit = {
+// makes this class thread-safe:
+// only the first thread entering this block can set sparkSession
+// all other threads will see the exception, as it is only allowed to do
this once
+synchronized {
+ if (this.sparkSession.isDefined) {
+throw new IllegalArgumentException("An Observation can be used with a
Dataset only once")
+ }
+ this.sparkSession = Some(sparkSession)
+}
+
+sparkSession.listenerManager.register(this.listener)
+ }
+
+ private def unregister(): Unit = {
+this.sparkSession.foreach(_.listenerManager.unregister(this.listener))
+ }
+
+ private[spark] def onFinish(qe: QueryExecution): Unit = {
+synchronized {
+ if (this.row.isEmpty) {
+this.row = qe.observedMetrics.get(name)
+if (this.row.isDefined) {
+ notifyAll()
+ unregister()
+}
+ }
+}
+ }
+
+}
+
+private[sql] case class ObservationListener(observation: Observation)
+ extends QueryExecutionListener {
+
+ override def onSuccess(funcName: String, qe: QueryExecution, durationNs:
Long): Unit =
+observation.onFinish(qe)
+
+ override def onFailure(funcName: String, qe: QueryExecution, exception:
Exception): Unit =
+observation.onFinish(qe)
+
+}
+
+/**
+ * (Scala-specific) Create a named or anonym
[GitHub] [spark] HyukjinKwon commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
HyukjinKwon commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r672800470
##
File path: sql/core/src/main/scala/org/apache/spark/sql/Observation.scala
##
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+
+import java.util.UUID
+
+import org.apache.spark.sql.execution.QueryExecution
+import org.apache.spark.sql.util.QueryExecutionListener
+
+
+/**
+ * Helper class to simplify usage of `Dataset.observe(String, Column,
Column*)`:
+ *
+ * {{{
+ * // Observe row count (rows) and highest id (maxid) in the Dataset while
writing it
+ * val observation = Observation("my metrics")
+ * val observed_ds = ds.observe(observation, count(lit(1)).as("rows"),
max($"id").as("maxid"))
+ * observed_ds.write.parquet("ds.parquet")
+ * val metrics = observation.get
+ * }}}
+ *
+ * This collects the metrics while the first action is executed on the
observed dataset. Subsequent
+ * actions do not modify the metrics returned by [[get]]. Retrieval of the
metric via [[get]]
+ * blocks until the first action has finished and metrics become available.
+ *
+ * This class does not support streaming datasets.
+ *
+ * @param name name of the metric
+ * @since 3.3.0
+ */
+class Observation(name: String) {
+
+ private val listener: ObservationListener = ObservationListener(this)
+
+ @volatile private var sparkSession: Option[SparkSession] = None
+
+ @volatile private var row: Option[Row] = None
+
+ /**
+ * Attach this observation to the given [[Dataset]] to observe aggregation
expressions.
+ *
+ * @param ds dataset
+ * @param expr first aggregation expression
+ * @param exprs more aggregation expressions
+ * @tparam T dataset type
+ * @return observed dataset
+ * @throws IllegalArgumentException If this is a streaming Dataset
(ds.isStreaming == true)
+ */
+ private[spark] def on[T](ds: Dataset[T], expr: Column, exprs: Column*):
Dataset[T] = {
+if (ds.isStreaming) {
+ throw new IllegalArgumentException("Observation does not support
streaming Datasets")
+}
+register(ds.sparkSession)
+ds.observe(name, expr, exprs: _*)
+ }
+
+ /**
+ * Get the observed metrics. This waits for the observed dataset to finish
its first action.
+ * Only the result of the first action is available. Subsequent actions do
not modify the result.
+ *
+ * @return the observed metrics as a [[Row]]
+ * @throws InterruptedException interrupted while waiting
+ */
+ @throws[InterruptedException]
+ def get: Row = {
+synchronized {
+ // we need to loop as wait might return without us calling notify
+ //
https://en.wikipedia.org/w/index.php?title=Spurious_wakeup&oldid=992601610
+ while (this.row.isEmpty) {
+wait()
+ }
+}
+
+this.row.get
+ }
+
+ private def register(sparkSession: SparkSession): Unit = {
+// makes this class thread-safe:
+// only the first thread entering this block can set sparkSession
+// all other threads will see the exception, as it is only allowed to do
this once
+synchronized {
+ if (this.sparkSession.isDefined) {
+throw new IllegalArgumentException("An Observation can be used with a
Dataset only once")
+ }
+ this.sparkSession = Some(sparkSession)
+}
+
+sparkSession.listenerManager.register(this.listener)
+ }
+
+ private def unregister(): Unit = {
+this.sparkSession.foreach(_.listenerManager.unregister(this.listener))
+ }
+
+ private[spark] def onFinish(qe: QueryExecution): Unit = {
+synchronized {
+ if (this.row.isEmpty) {
+this.row = qe.observedMetrics.get(name)
+if (this.row.isDefined) {
+ notifyAll()
+ unregister()
+}
+ }
+}
+ }
+
+}
+
+private[sql] case class ObservationListener(observation: Observation)
+ extends QueryExecutionListener {
+
+ override def onSuccess(funcName: String, qe: QueryExecution, durationNs:
Long): Unit =
+observation.onFinish(qe)
+
+ override def onFailure(funcName: String, qe: QueryExecution, exception:
Exception): Unit =
+observation.onFinish(qe)
+
+}
+
+/**
+ * (Scala-specific) Create a named or anonym
[GitHub] [spark] HyukjinKwon commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
HyukjinKwon commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r672721125
##
File path: sql/core/src/main/scala/org/apache/spark/sql/Observation.scala
##
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+
+import java.util.UUID
+
+import org.apache.spark.sql.execution.QueryExecution
+import org.apache.spark.sql.util.QueryExecutionListener
+
+
+/**
+ * Helper class to simplify usage of `Dataset.observe(String, Column,
Column*)`:
+ *
+ * {{{
+ * // Observe row count (rows) and highest id (maxid) in the Dataset while
writing it
+ * val observation = Observation("my metrics")
+ * val observed_ds = ds.observe(observation, count(lit(1)).as("rows"),
max($"id").as("maxid"))
+ * observed_ds.write.parquet("ds.parquet")
+ * val metrics = observation.get
+ * }}}
+ *
+ * This collects the metrics while the first action is executed on the
observed dataset. Subsequent
+ * actions do not modify the metrics returned by [[get]]. Retrieval of the
metric via [[get]]
+ * blocks until the first action has finished and metrics become available.
+ *
+ * This class does not support streaming datasets.
+ *
+ * @param name name of the metric
+ * @since 3.3.0
+ */
+class Observation(name: String) {
+
+ private val listener: ObservationListener = ObservationListener(this)
+
+ @volatile private var sparkSession: Option[SparkSession] = None
+
+ @volatile private var row: Option[Row] = None
+
+ /**
+ * Attach this observation to the given [[Dataset]] to observe aggregation
expressions.
+ *
+ * @param ds dataset
+ * @param expr first aggregation expression
+ * @param exprs more aggregation expressions
+ * @tparam T dataset type
+ * @return observed dataset
+ * @throws IllegalArgumentException If this is a streaming Dataset
(ds.isStreaming == true)
+ */
+ private[spark] def on[T](ds: Dataset[T], expr: Column, exprs: Column*):
Dataset[T] = {
+if (ds.isStreaming) {
+ throw new IllegalArgumentException("Observation does not support
streaming Datasets")
+}
+register(ds.sparkSession)
+ds.observe(name, expr, exprs: _*)
+ }
+
+ /**
+ * Get the observed metrics. This waits for the observed dataset to finish
its first action.
+ * Only the result of the first action is available. Subsequent actions do
not modify the result.
+ *
+ * @return the observed metrics as a [[Row]]
+ * @throws InterruptedException interrupted while waiting
+ */
+ @throws[InterruptedException]
+ def get: Row = {
+synchronized {
+ // we need to loop as wait might return without us calling notify
+ //
https://en.wikipedia.org/w/index.php?title=Spurious_wakeup&oldid=992601610
+ while (this.row.isEmpty) {
+wait()
+ }
+}
+
+this.row.get
+ }
+
+ private def register(sparkSession: SparkSession): Unit = {
+// makes this class thread-safe:
+// only the first thread entering this block can set sparkSession
+// all other threads will see the exception, as it is only allowed to do
this once
+synchronized {
+ if (this.sparkSession.isDefined) {
+throw new IllegalArgumentException("An Observation can be used with a
Dataset only once")
+ }
+ this.sparkSession = Some(sparkSession)
+}
+
+sparkSession.listenerManager.register(this.listener)
+ }
+
+ private def unregister(): Unit = {
+this.sparkSession.foreach(_.listenerManager.unregister(this.listener))
+ }
+
+ private[spark] def onFinish(qe: QueryExecution): Unit = {
+synchronized {
+ if (this.row.isEmpty) {
+this.row = qe.observedMetrics.get(name)
+if (this.row.isDefined) {
+ notifyAll()
+ unregister()
+}
+ }
+}
+ }
+
+}
+
+private[sql] case class ObservationListener(observation: Observation)
+ extends QueryExecutionListener {
+
+ override def onSuccess(funcName: String, qe: QueryExecution, durationNs:
Long): Unit =
+observation.onFinish(qe)
+
+ override def onFailure(funcName: String, qe: QueryExecution, exception:
Exception): Unit =
+observation.onFinish(qe)
+
+}
+
+/**
+ * (Scala-specific) Create a named or anonym
