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Posted to reviews@spark.apache.org by gatorsmile <gi...@git.apache.org> on 2018/01/29 02:02:53 UTC
[GitHub] spark pull request #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Descript...
GitHub user gatorsmile opened a pull request:
https://github.com/apache/spark/pull/20420
[SPARK-22916][SQL][FOLLOW-UP] Update the Description of Join Selection
## What changes were proposed in this pull request?
This PR is to update the description of the join algorithm changes.
## How was this patch tested?
N/A
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/gatorsmile/spark followUp22916
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/20420.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 #20420
----
commit ac8b1bcea76368ff27de30b1696694dadde7e658
Author: gatorsmile <ga...@...>
Date: 2018-01-29T02:01:22Z
fix
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[GitHub] spark issue #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Description of ...
Posted by gatorsmile <gi...@git.apache.org>.
Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/20420
retest this please
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[GitHub] spark issue #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Description of ...
Posted by liufengdb <gi...@git.apache.org>.
Github user liufengdb commented on the issue:
https://github.com/apache/spark/pull/20420
LGTM! Thanks for doing this!
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[GitHub] spark issue #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Description of ...
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[GitHub] spark issue #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Description of ...
Posted by gatorsmile <gi...@git.apache.org>.
Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/20420
`org.apache.spark.sql.execution.datasources.orc.OrcQuerySuite.(It is not a test it is a sbt.testing.SuiteSelector)` is another flaky test
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**[Test build #86753 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/86753/testReport)** for PR 20420 at commit [`ac8b1bc`](https://github.com/apache/spark/commit/ac8b1bcea76368ff27de30b1696694dadde7e658).
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[GitHub] spark issue #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Description of ...
Posted by SparkQA <gi...@git.apache.org>.
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https://github.com/apache/spark/pull/20420
**[Test build #86771 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/86771/testReport)** for PR 20420 at commit [`ac8b1bc`](https://github.com/apache/spark/commit/ac8b1bcea76368ff27de30b1696694dadde7e658).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark issue #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Description of ...
Posted by gatorsmile <gi...@git.apache.org>.
Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/20420
Thanks! Merged to master/2.3.
This PR is just to reflect the latest changes in the join selection rule. We can continue the improvement in the comment.
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[GitHub] spark issue #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Description of ...
Posted by cloud-fan <gi...@git.apache.org>.
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/20420
retest this please
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[GitHub] spark pull request #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Descript...
Posted by gatorsmile <gi...@git.apache.org>.
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/20420#discussion_r164327644
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala ---
@@ -91,23 +91,58 @@ abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
* Select the proper physical plan for join based on joining keys and size of logical plan.
*
* At first, uses the [[ExtractEquiJoinKeys]] pattern to find joins where at least some of the
- * predicates can be evaluated by matching join keys. If found, Join implementations are chosen
+ * predicates can be evaluated by matching join keys. If found, join implementations are chosen
* with the following precedence:
*
- * - Broadcast: We prefer to broadcast the join side with an explicit broadcast hint(e.g. the
- * user applied the [[org.apache.spark.sql.functions.broadcast()]] function to a DataFrame).
- * If both sides have the broadcast hint, we prefer to broadcast the side with a smaller
- * estimated physical size. If neither one of the sides has the broadcast hint,
- * we only broadcast the join side if its estimated physical size that is smaller than
- * the user-configurable [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]] threshold.
+ * - Broadcast hash join (BHJ):
+ * BHJ is not supported for full outer join. For right outer join, we only can broadcast the
+ * left side. For left outer, left semi, left anti and the internal join type ExistenceJoin,
+ * we only can broadcast the right side. For inner like join, we can broadcast both sides.
+ * Normally, BHJ can perform faster than the other join algorithms when the broadcast side is
+ * small. However, broadcasting tables is a network-intensive operation. It could cause OOM
+ * or perform worse than the other join algorithms, especially when the build/broadcast side
+ * is big.
+ *
+ * For the supported cases, users can specify the broadcast hint (e.g. the user applied the
+ * [[org.apache.spark.sql.functions.broadcast()]] function to a DataFrame) and session-based
+ * [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]] threshold to adjust whether BHJ is used and
+ * which join side is broadcast.
+ *
+ * 1) Broadcast the join side with the broadcast hint, even if the size is larger than
+ * [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]]. If both sides have the hint (only when the type
+ * is inner like join), the side with a smaller estimated physical size will be broadcast.
+ * 2) Respect the [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]] threshold and broadcast the side
+ * whose estimated physical size is smaller than the threshold. If both sides are below the
+ * threshold, broadcast the smaller side. If neither is smaller, BHJ is not used.
+ *
* - Shuffle hash join: if the average size of a single partition is small enough to build a hash
* table.
+ *
* - Sort merge: if the matching join keys are sortable.
*
* If there is no joining keys, Join implementations are chosen with the following precedence:
- * - BroadcastNestedLoopJoin: if one side of the join could be broadcasted
- * - CartesianProduct: for Inner join
- * - BroadcastNestedLoopJoin
+ * - BroadcastNestedLoopJoin (BNLJ):
+ * BNLJ supports all the join types but the impl is OPTIMIZED for the following scenarios:
+ * For right outer join, the left side is broadcast. For left outer, left semi, left anti
+ * and the internal join type ExistenceJoin, the right side is broadcast. For inner like
+ * joins, either side is broadcast.
+ *
+ * Like BHJ, users still can specify the broadcast hint and session-based
+ * [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]] threshold to impact which side is broadcast.
+ *
+ * 1) Broadcast the join side with the broadcast hint, even if the size is larger than
+ * [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]]. If both sides have the hint (i.e., just for
+ * inner-like join), the side with a smaller estimated physical size will be broadcast.
+ * 2) Respect the [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]] threshold and broadcast the side
+ * whose estimated physical size is smaller than the threshold. If both sides are below the
+ * threshold, broadcast the smaller side. If neither is smaller, BNLJ is not used.
+ *
+ * - CartesianProduct: for inner like join, CartesianProduct is the fallback option.
+ *
+ * - BroadcastNestedLoopJoin (BNLJ):
--- End diff --
This is based on the order of our JoinSelection rule
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[GitHub] spark issue #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Description of ...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/20420
**[Test build #86747 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/86747/testReport)** for PR 20420 at commit [`ac8b1bc`](https://github.com/apache/spark/commit/ac8b1bcea76368ff27de30b1696694dadde7e658).
* This patch **fails Spark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Descript...
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
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[GitHub] spark pull request #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Descript...
Posted by cloud-fan <gi...@git.apache.org>.
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/20420#discussion_r164326386
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala ---
@@ -91,23 +91,58 @@ abstract class SparkStrategies extends QueryPlanner[SparkPlan] {
* Select the proper physical plan for join based on joining keys and size of logical plan.
*
* At first, uses the [[ExtractEquiJoinKeys]] pattern to find joins where at least some of the
- * predicates can be evaluated by matching join keys. If found, Join implementations are chosen
+ * predicates can be evaluated by matching join keys. If found, join implementations are chosen
* with the following precedence:
*
- * - Broadcast: We prefer to broadcast the join side with an explicit broadcast hint(e.g. the
- * user applied the [[org.apache.spark.sql.functions.broadcast()]] function to a DataFrame).
- * If both sides have the broadcast hint, we prefer to broadcast the side with a smaller
- * estimated physical size. If neither one of the sides has the broadcast hint,
- * we only broadcast the join side if its estimated physical size that is smaller than
- * the user-configurable [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]] threshold.
+ * - Broadcast hash join (BHJ):
+ * BHJ is not supported for full outer join. For right outer join, we only can broadcast the
+ * left side. For left outer, left semi, left anti and the internal join type ExistenceJoin,
+ * we only can broadcast the right side. For inner like join, we can broadcast both sides.
+ * Normally, BHJ can perform faster than the other join algorithms when the broadcast side is
+ * small. However, broadcasting tables is a network-intensive operation. It could cause OOM
+ * or perform worse than the other join algorithms, especially when the build/broadcast side
+ * is big.
+ *
+ * For the supported cases, users can specify the broadcast hint (e.g. the user applied the
+ * [[org.apache.spark.sql.functions.broadcast()]] function to a DataFrame) and session-based
+ * [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]] threshold to adjust whether BHJ is used and
+ * which join side is broadcast.
+ *
+ * 1) Broadcast the join side with the broadcast hint, even if the size is larger than
+ * [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]]. If both sides have the hint (only when the type
+ * is inner like join), the side with a smaller estimated physical size will be broadcast.
+ * 2) Respect the [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]] threshold and broadcast the side
+ * whose estimated physical size is smaller than the threshold. If both sides are below the
+ * threshold, broadcast the smaller side. If neither is smaller, BHJ is not used.
+ *
* - Shuffle hash join: if the average size of a single partition is small enough to build a hash
* table.
+ *
* - Sort merge: if the matching join keys are sortable.
*
* If there is no joining keys, Join implementations are chosen with the following precedence:
- * - BroadcastNestedLoopJoin: if one side of the join could be broadcasted
- * - CartesianProduct: for Inner join
- * - BroadcastNestedLoopJoin
+ * - BroadcastNestedLoopJoin (BNLJ):
+ * BNLJ supports all the join types but the impl is OPTIMIZED for the following scenarios:
+ * For right outer join, the left side is broadcast. For left outer, left semi, left anti
+ * and the internal join type ExistenceJoin, the right side is broadcast. For inner like
+ * joins, either side is broadcast.
+ *
+ * Like BHJ, users still can specify the broadcast hint and session-based
+ * [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]] threshold to impact which side is broadcast.
+ *
+ * 1) Broadcast the join side with the broadcast hint, even if the size is larger than
+ * [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]]. If both sides have the hint (i.e., just for
+ * inner-like join), the side with a smaller estimated physical size will be broadcast.
+ * 2) Respect the [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]] threshold and broadcast the side
+ * whose estimated physical size is smaller than the threshold. If both sides are below the
+ * threshold, broadcast the smaller side. If neither is smaller, BNLJ is not used.
+ *
+ * - CartesianProduct: for inner like join, CartesianProduct is the fallback option.
+ *
+ * - BroadcastNestedLoopJoin (BNLJ):
--- End diff --
`BroadcastNestedLoopJoin (BNLJ)` appeared twice in this list, is it intentional?
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[GitHub] spark issue #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Description of ...
Posted by gatorsmile <gi...@git.apache.org>.
Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/20420
cc @liufengdb @cloud-fan
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* This patch **fails due to an unknown error code, -9**.
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[GitHub] spark issue #20420: [SPARK-22916][SQL][FOLLOW-UP] Update the Description of ...
Posted by cloud-fan <gi...@git.apache.org>.
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/20420
maybe we should separate the distribution concern and algorithm concern from the join selection when documenting it:
* for distribution concern, we can do broadcast, shuffle or cartesian
* for algorithm concern, we can do hash join, sort merge join or nested loop join.
By combining these 2 concerns, we get many different join selections(exclude some invalid combinations):
* broadcast hash join
* broadcast nested loop join
* (shuffled) sort merge join
* shuffled hash join
* cartesian product (nested loop join)
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