[GitHub] [spark] cloud-fan commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
cloud-fan commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r673102271
##
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:
if it's simply adding an annotation `@varargs`, shall we just do it in
this PR?
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[GitHub] [spark] cloud-fan commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
cloud-fan commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r672777257
##
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 anonymou
[GitHub] [spark] cloud-fan commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
cloud-fan commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r672777257
##
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 anonymou
[GitHub] [spark] cloud-fan commented on a change in pull request #33422: [SPARK-34806][SQL] Add Observation helper for Dataset.observe
cloud-fan commented on a change in pull request #33422:
URL: https://github.com/apache/spark/pull/33422#discussion_r672777257
##
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 anonymou
