[SPARK-23406] [SS] Enable stream-stream self-joins #20598
Closed
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Test build #87388 has finished for PR 20598 at commit
|
marmbrus
approved these changes
Feb 13, 2018
| @@ -431,7 +431,11 @@ class MicroBatchExecution( | |||
| s"Invalid batch: ${Utils.truncatedString(output, ",")} != " + | |||
| s"${Utils.truncatedString(dataPlan.output, ",")}") | |||
| replacements ++= output.zip(dataPlan.output) | |||
There was a problem hiding this comment.
I think this is no longer used.
| @@ -440,8 +444,6 @@ class MicroBatchExecution( | |||
| // Rewire the plan to use the new attributes that were returned by the source. | |||
| val replacementMap = AttributeMap(replacements) | |||
cloud-fan
reviewed
Feb 14, 2018
| @@ -62,7 +64,7 @@ case class StreamingRelation(dataSource: DataSource, sourceName: String, output: | |||
| case class StreamingExecutionRelation( | |||
There was a problem hiding this comment.
not very familiar with the streaming side, but IIRC, some of these plans are temporary and will be replaced before entering analyzer, and these plans don't need to extend MultiInstanceRelation.
There was a problem hiding this comment.
They need to extend MultiInstance relation, because Dataset.join() forces an analysis to disambiguate left and right in self-joins (here) and when there is a self-join between two streaming Datasets (i.e. they contain StreamingRelation/StreamingRelationV2), without the MultiInstanceRelation, it throws the error (see PR description).
Regarding StreamingExecutionRelation, while the other sources convert StreamingRelation to StreamingExecutionRelation, the MemoryStream directly injects StreamingExceutionRelation at that time of Dataset operations. Hence its good that StreamingExecutionRelation also extends MultiInstanceRelation.
|
Test build #87443 has finished for PR 20598 at commit
|
|
Are we waiting for the RC to pass before backporting this one to 2.3? |
|
Yeah, this seems risky at RC5. |
|
This is a slightly invasive change in the engine, hence I was not planning
to backport.
Also, I realized after this PR that self-joins mostly actually work except
in few corner cases which I accidentally hit. And even if you hit them and
get the error in the JIRA, for most of them, you can add projects in your
code to get around them.
…On Wed, Feb 21, 2018 at 9:33 AM, Wenchen Fan ***@***.***> wrote:
Are we waiting for the RC to pass before backporting this one to 2.3?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
<#20598 (comment)>, or mute
the thread
<https://github.com/notifications/unsubscribe-auth/AAoerOrJkZfc0I7HH7j1qEY6vGr6E8bMks5tXFNSgaJpZM4SDenO>
.
|
tdas
added a commit
to tdas/spark
that referenced
this pull request
Mar 8, 2018
## What changes were proposed in this pull request?
Solved two bugs to enable stream-stream self joins.
### Incorrect analysis due to missing MultiInstanceRelation trait
Streaming leaf nodes did not extend MultiInstanceRelation, which is necessary for the catalyst analyzer to convert the self-join logical plan DAG into a tree (by creating new instances of the leaf relations). This was causing the error `Failure when resolving conflicting references in Join:` (see JIRA for details).
### Incorrect attribute rewrite when splicing batch plans in MicroBatchExecution
When splicing the source's batch plan into the streaming plan (by replacing the StreamingExecutionPlan), we were rewriting the attribute reference in the streaming plan with the new attribute references from the batch plan. This was incorrectly handling the scenario when multiple StreamingExecutionRelation point to the same source, and therefore eventually point to the same batch plan returned by the source. Here is an example query, and its corresponding plan transformations.
```
val df = input.toDF
val join =
df.select('value % 5 as "key", 'value).join(
df.select('value % 5 as "key", 'value), "key")
```
Streaming logical plan before splicing the batch plan
```
Project [key#6, value#1, value#12]
+- Join Inner, (key#6 = key#9)
:- Project [(value#1 % 5) AS key#6, value#1]
: +- StreamingExecutionRelation Memory[#1], value#1
+- Project [(value#12 % 5) AS key#9, value#12]
+- StreamingExecutionRelation Memory[#1], value#12 // two different leaves pointing to same source
```
Batch logical plan after splicing the batch plan and before rewriting
```
Project [key#6, value#1, value#12]
+- Join Inner, (key#6 = key#9)
:- Project [(value#1 % 5) AS key#6, value#1]
: +- LocalRelation [value#66] // replaces StreamingExecutionRelation Memory[#1], value#1
+- Project [(value#12 % 5) AS key#9, value#12]
+- LocalRelation [value#66] // replaces StreamingExecutionRelation Memory[#1], value#12
```
Batch logical plan after rewriting the attributes. Specifically, for spliced, the new output attributes (value#66) replace the earlier output attributes (value#12, and value#1, one for each StreamingExecutionRelation).
```
Project [key#6, value#66, value#66] // both value#1 and value#12 replaces by value#66
+- Join Inner, (key#6 = key#9)
:- Project [(value#66 % 5) AS key#6, value#66]
: +- LocalRelation [value#66]
+- Project [(value#66 % 5) AS key#9, value#66]
+- LocalRelation [value#66]
```
This causes the optimizer to eliminate value#66 from one side of the join.
```
Project [key#6, value#66, value#66]
+- Join Inner, (key#6 = key#9)
:- Project [(value#66 % 5) AS key#6, value#66]
: +- LocalRelation [value#66]
+- Project [(value#66 % 5) AS key#9] // this does not generate value, incorrect join results
+- LocalRelation [value#66]
```
**Solution**: Instead of rewriting attributes, use a Project to introduce aliases between the output attribute references and the new reference generated by the spliced plans. The analyzer and optimizer will take care of the rest.
```
Project [key#6, value#1, value#12]
+- Join Inner, (key#6 = key#9)
:- Project [(value#1 % 5) AS key#6, value#1]
: +- Project [value#66 AS value#1] // solution: project with aliases
: +- LocalRelation [value#66]
+- Project [(value#12 % 5) AS key#9, value#12]
+- Project [value#66 AS value#12] // solution: project with aliases
+- LocalRelation [value#66]
```
## How was this patch tested?
New unit test
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes apache#20598 from tdas/SPARK-23406.
asfgit
pushed a commit
that referenced
this pull request
Mar 8, 2018
This is a backport of #20598. ## What changes were proposed in this pull request? Solved two bugs to enable stream-stream self joins. ### Incorrect analysis due to missing MultiInstanceRelation trait Streaming leaf nodes did not extend MultiInstanceRelation, which is necessary for the catalyst analyzer to convert the self-join logical plan DAG into a tree (by creating new instances of the leaf relations). This was causing the error `Failure when resolving conflicting references in Join:` (see JIRA for details). ### Incorrect attribute rewrite when splicing batch plans in MicroBatchExecution When splicing the source's batch plan into the streaming plan (by replacing the StreamingExecutionPlan), we were rewriting the attribute reference in the streaming plan with the new attribute references from the batch plan. This was incorrectly handling the scenario when multiple StreamingExecutionRelation point to the same source, and therefore eventually point to the same batch plan returned by the source. Here is an example query, and its corresponding plan transformations. ``` val df = input.toDF val join = df.select('value % 5 as "key", 'value).join( df.select('value % 5 as "key", 'value), "key") ``` Streaming logical plan before splicing the batch plan ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- StreamingExecutionRelation Memory[#1], value#1 +- Project [(value#12 % 5) AS key#9, value#12] +- StreamingExecutionRelation Memory[#1], value#12 // two different leaves pointing to same source ``` Batch logical plan after splicing the batch plan and before rewriting ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- LocalRelation [value#66] // replaces StreamingExecutionRelation Memory[#1], value#1 +- Project [(value#12 % 5) AS key#9, value#12] +- LocalRelation [value#66] // replaces StreamingExecutionRelation Memory[#1], value#12 ``` Batch logical plan after rewriting the attributes. Specifically, for spliced, the new output attributes (value#66) replace the earlier output attributes (value#12, and value#1, one for each StreamingExecutionRelation). ``` Project [key#6, value#66, value#66] // both value#1 and value#12 replaces by value#66 +- Join Inner, (key#6 = key#9) :- Project [(value#66 % 5) AS key#6, value#66] : +- LocalRelation [value#66] +- Project [(value#66 % 5) AS key#9, value#66] +- LocalRelation [value#66] ``` This causes the optimizer to eliminate value#66 from one side of the join. ``` Project [key#6, value#66, value#66] +- Join Inner, (key#6 = key#9) :- Project [(value#66 % 5) AS key#6, value#66] : +- LocalRelation [value#66] +- Project [(value#66 % 5) AS key#9] // this does not generate value, incorrect join results +- LocalRelation [value#66] ``` **Solution**: Instead of rewriting attributes, use a Project to introduce aliases between the output attribute references and the new reference generated by the spliced plans. The analyzer and optimizer will take care of the rest. ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- Project [value#66 AS value#1] // solution: project with aliases : +- LocalRelation [value#66] +- Project [(value#12 % 5) AS key#9, value#12] +- Project [value#66 AS value#12] // solution: project with aliases +- LocalRelation [value#66] ``` ## How was this patch tested? New unit test Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #20765 from tdas/SPARK-23406-2.3.
peter-toth
pushed a commit
to peter-toth/spark
that referenced
this pull request
Oct 6, 2018
This is a backport of apache#20598. ## What changes were proposed in this pull request? Solved two bugs to enable stream-stream self joins. ### Incorrect analysis due to missing MultiInstanceRelation trait Streaming leaf nodes did not extend MultiInstanceRelation, which is necessary for the catalyst analyzer to convert the self-join logical plan DAG into a tree (by creating new instances of the leaf relations). This was causing the error `Failure when resolving conflicting references in Join:` (see JIRA for details). ### Incorrect attribute rewrite when splicing batch plans in MicroBatchExecution When splicing the source's batch plan into the streaming plan (by replacing the StreamingExecutionPlan), we were rewriting the attribute reference in the streaming plan with the new attribute references from the batch plan. This was incorrectly handling the scenario when multiple StreamingExecutionRelation point to the same source, and therefore eventually point to the same batch plan returned by the source. Here is an example query, and its corresponding plan transformations. ``` val df = input.toDF val join = df.select('value % 5 as "key", 'value).join( df.select('value % 5 as "key", 'value), "key") ``` Streaming logical plan before splicing the batch plan ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- StreamingExecutionRelation Memory[#1], value#1 +- Project [(value#12 % 5) AS key#9, value#12] +- StreamingExecutionRelation Memory[#1], value#12 // two different leaves pointing to same source ``` Batch logical plan after splicing the batch plan and before rewriting ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- LocalRelation [value#66] // replaces StreamingExecutionRelation Memory[#1], value#1 +- Project [(value#12 % 5) AS key#9, value#12] +- LocalRelation [value#66] // replaces StreamingExecutionRelation Memory[#1], value#12 ``` Batch logical plan after rewriting the attributes. Specifically, for spliced, the new output attributes (value#66) replace the earlier output attributes (value#12, and value#1, one for each StreamingExecutionRelation). ``` Project [key#6, value#66, value#66] // both value#1 and value#12 replaces by value#66 +- Join Inner, (key#6 = key#9) :- Project [(value#66 % 5) AS key#6, value#66] : +- LocalRelation [value#66] +- Project [(value#66 % 5) AS key#9, value#66] +- LocalRelation [value#66] ``` This causes the optimizer to eliminate value#66 from one side of the join. ``` Project [key#6, value#66, value#66] +- Join Inner, (key#6 = key#9) :- Project [(value#66 % 5) AS key#6, value#66] : +- LocalRelation [value#66] +- Project [(value#66 % 5) AS key#9] // this does not generate value, incorrect join results +- LocalRelation [value#66] ``` **Solution**: Instead of rewriting attributes, use a Project to introduce aliases between the output attribute references and the new reference generated by the spliced plans. The analyzer and optimizer will take care of the rest. ``` Project [key#6, value#1, value#12] +- Join Inner, (key#6 = key#9) :- Project [(value#1 % 5) AS key#6, value#1] : +- Project [value#66 AS value#1] // solution: project with aliases : +- LocalRelation [value#66] +- Project [(value#12 % 5) AS key#9, value#12] +- Project [value#66 AS value#12] // solution: project with aliases +- LocalRelation [value#66] ``` ## How was this patch tested? New unit test Author: Tathagata Das <tathagata.das1565@gmail.com> Closes apache#20765 from tdas/SPARK-23406-2.3.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
What changes were proposed in this pull request?
Solved two bugs to enable stream-stream self joins.
Incorrect analysis due to missing MultiInstanceRelation trait
Streaming leaf nodes did not extend MultiInstanceRelation, which is necessary for the catalyst analyzer to convert the self-join logical plan DAG into a tree (by creating new instances of the leaf relations). This was causing the error
Failure when resolving conflicting references in Join:(see JIRA for details).Incorrect attribute rewrite when splicing batch plans in MicroBatchExecution
When splicing the source's batch plan into the streaming plan (by replacing the StreamingExecutionPlan), we were rewriting the attribute reference in the streaming plan with the new attribute references from the batch plan. This was incorrectly handling the scenario when multiple StreamingExecutionRelation point to the same source, and therefore eventually point to the same batch plan returned by the source. Here is an example query, and its corresponding plan transformations.
Streaming logical plan before splicing the batch plan
Batch logical plan after splicing the batch plan and before rewriting
Batch logical plan after rewriting the attributes. Specifically, for spliced, the new output attributes (value#66) replace the earlier output attributes (value#12, and value#1, one for each StreamingExecutionRelation).
This causes the optimizer to eliminate value#66 from one side of the join.
Solution: Instead of rewriting attributes, use a Project to introduce aliases between the output attribute references and the new reference generated by the spliced plans. The analyzer and optimizer will take care of the rest.
How was this patch tested?
New unit test