[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
Github user andrewor14 commented on the pull request: https://github.com/apache/spark/pull/2839#issuecomment-59991158 Ok I'm merging this thanks. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
Github user mateiz commented on the pull request: https://github.com/apache/spark/pull/2839#issuecomment-59822350 LGTM provided it passes tests. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
GitHub user aarondav opened a pull request: https://github.com/apache/spark/pull/2839 [SPARK-3994] Use standard Aggregator code path for countByKey and countByValue See [JIRA](https://issues.apache.org/jira/browse/SPARK-3994) for more information. Also adds a note which warns against using these methods. You can merge this pull request into a Git repository by running: $ git pull https://github.com/aarondav/spark countByKey Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/2839.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #2839 commit e1f06d3c550e5419bb3b20745da7cbfdedbb2841 Author: Aaron Davidson aa...@databricks.com Date: 2014-10-17T22:11:25Z [SPARK-3994] Use standard Aggregator code path for countByKey and countByValue See [JIRA](https://issues.apache.org/jira/browse/SPARK-3994) for more information. Also adds a note which warns against using these methods. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
Github user aarondav commented on a diff in the pull request:
https://github.com/apache/spark/pull/2839#discussion_r19046865
--- Diff: core/src/main/scala/org/apache/spark/rdd/RDD.scala ---
@@ -911,32 +911,15 @@ abstract class RDD[T: ClassTag](
}
/**
- * Return the count of each unique value in this RDD as a map of (value,
count) pairs. The final
- * combine step happens locally on the master, equivalent to running a
single reduce task.
+ * Return the count of each unique value in this RDD as a local map of
(value, count) pairs.
+ *
+ * Note that this method should only be used if the resulting map is
expected to be small, as
+ * the whole thing is loaded into the driver's memory.
+ * To handle very large results, consider using rdd.map(x = (x,
1)).reduceByKey(_ + _), which
+ * returns an RDD[T, Long] instead of a map.
*/
def countByValue()(implicit ord: Ordering[T] = null): Map[T, Long] = {
-if (elementClassTag.runtimeClass.isArray) {
- throw new SparkException(countByValue() does not support arrays)
--- End diff --
Note that we still don't support arrays, but this is caught by combineByKey:
`org.apache.spark.SparkException: Cannot use map-side combining with array
keys.`
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
Github user aarondav commented on the pull request: https://github.com/apache/spark/pull/2839#issuecomment-59584036 @pwendell If you get a chance, PTAL --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
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[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
Github user andrewor14 commented on a diff in the pull request: https://github.com/apache/spark/pull/2839#discussion_r19051173 --- Diff: core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala --- @@ -238,8 +238,15 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) @deprecated(Use reduceByKeyLocally, 1.0.0) def reduceByKeyToDriver(func: (V, V) = V): Map[K, V] = reduceByKeyLocally(func) - /** Count the number of elements for each key, and return the result to the master as a Map. */ - def countByKey(): Map[K, Long] = self.map(_._1).countByValue() + /** + * Count the number of elements for each key, collecting the results to a local Map. + * + * Note that this method should only be used if the resulting map is expected to be small, as + * the whole thing is loaded into the driver's memory. + * To handle very large results, consider using rdd.mapValues(_ = 1).reduceByKey(_ + _), which --- End diff -- 1L --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
Github user andrewor14 commented on a diff in the pull request: https://github.com/apache/spark/pull/2839#discussion_r19051176 --- Diff: core/src/main/scala/org/apache/spark/rdd/RDD.scala --- @@ -911,32 +911,15 @@ abstract class RDD[T: ClassTag]( } /** - * Return the count of each unique value in this RDD as a map of (value, count) pairs. The final - * combine step happens locally on the master, equivalent to running a single reduce task. + * Return the count of each unique value in this RDD as a local map of (value, count) pairs. + * + * Note that this method should only be used if the resulting map is expected to be small, as + * the whole thing is loaded into the driver's memory. + * To handle very large results, consider using rdd.map(x = (x, 1)).reduceByKey(_ + _), which --- End diff -- 1L --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
Github user andrewor14 commented on a diff in the pull request: https://github.com/apache/spark/pull/2839#discussion_r19051180 --- Diff: core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala --- @@ -238,8 +238,15 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) @deprecated(Use reduceByKeyLocally, 1.0.0) def reduceByKeyToDriver(func: (V, V) = V): Map[K, V] = reduceByKeyLocally(func) - /** Count the number of elements for each key, and return the result to the master as a Map. */ - def countByKey(): Map[K, Long] = self.map(_._1).countByValue() + /** + * Count the number of elements for each key, collecting the results to a local Map. + * + * Note that this method should only be used if the resulting map is expected to be small, as + * the whole thing is loaded into the driver's memory. + * To handle very large results, consider using rdd.mapValues(_ = 1).reduceByKey(_ + _), which + * returns an RDD[T, Long] instead of a map. + */ + def countByKey(): Map[K, Long] = self.mapValues(_ = 1L).reduceByKey(_ + _).collect.toMap --- End diff -- think you need `collect()` --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-3994] Use standard Aggregator code path...
Github user andrewor14 commented on the pull request: https://github.com/apache/spark/pull/2839#issuecomment-59595776 LGTM. I think @mateiz wrote the original code so maybe he can take a look. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
