[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-19 Thread wzhfy
Github user wzhfy commented on the issue:

https://github.com/apache/spark/pull/17286
  
@ioana-delaney Thanks for the replies.

> Given A J1 B J2 C:   - case 1
• level 0: (A), (B), (C)
• level 1: {A, B}, ~~{A, C}~~, {B, C}
• level 3: {A, B, C}
Given A J1 B J2 C cross join D  - case 2
• level 0: (A), (B), (C), (D)
• level 1: {A, B}, ~~{A, C}, {A, D}~~, {B, C}, ~~{B, D}~~
• level 3: {A, B, C}, ~~{A, B, D}, {A, C, D}, {B, C, D}~~
• level 4: {A, B, C, D}

Currently the algorithm can prune cartesian products in case 1. For case 2, 
now it is based on the output of `ReorderJoin`, cartesian products are put at 
the end. So we have the same effect on the final plan.

In the future, we can merge these rules together.


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-18 Thread nsyca
Github user nsyca commented on the issue:

https://github.com/apache/spark/pull/17286
  
Right. I misread it. if there is no join predicate between a table and any 
cluster of tables, we should not consider that table in the join enumeration at 
all. We can simply push that table to be the last join.


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-18 Thread ioana-delaney
Github user ioana-delaney commented on the issue:

https://github.com/apache/spark/pull/17286
  
@gatorsmile Your example is correct. 

Given A J1 B J2 C:
• level 0: (A), (B), (C)
• level 1: {A, B}, ~{A, C}~, {B, C}
• level 3: {A, B, C}

Given A J1 B J2 C cross join D 
• level 0: (A), (B), (C), (D)
• level 1: {A, B}, ~{A, C}~, ~{A, D}~, {B, C}, ~{B, D}~
• level 3: {A, B, C}, ~{A, B, D}~, ~{A, C, D}~, ~{B, C, D}~
• level 4: {A, B, C, D}

The presence of join conditions between the outer-inner sets are good 
heuristics to be used during join enumeration.


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-18 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17286
  
My example is not related to inequality join or equi join.


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-18 Thread nsyca
Github user nsyca commented on the issue:

https://github.com/apache/spark/pull/17286
  
@gatorsmile An equality join in most cases has a better filtering than an 
inequality join. This can be used heuristically. However, this is not always 
true. An equality join can be a lookup join from a fact table to a dimension 
table that it does not reduce anything but an inequality join such as a range 
join over time period. 


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-18 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17286
  
Given {A, B, C} with the join conditions {A.a = B.b, B.b > C.c}. `{A, C}` 
should be pruned. 


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-18 Thread ioana-delaney
Github user ioana-delaney commented on the issue:

https://github.com/apache/spark/pull/17286
  
@wzhfy Given a set of input plans (either base table access or plans over 
derived/complex plans), one can build a graph based on the join conditions 
among the plans. I think join enumeration should be driven by the presence of 
join conditions between two plans. Following this approach, I think we can 
detect items that are not connected and plan them towards the end.


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-18 Thread wzhfy
Github user wzhfy commented on the issue:

https://github.com/apache/spark/pull/17286
  
@ioana-delaney How can we get disconnected parts before reordering? They 
can not only be leaf tables (this case is easier to deal with), but also 
subplans (tables can be joined internally but among subplans there's no join 
condition). We need to consider both cases and they may co-exist. Also, some 
disconnection can be eliminated by reordering.


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-18 Thread cloud-fan
Github user cloud-fan commented on the issue:

https://github.com/apache/spark/pull/17286
  
thanks, merging to master!


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-17 Thread ioana-delaney
Github user ioana-delaney commented on the issue:

https://github.com/apache/spark/pull/17286
  
@wzhfy Some thoughts on how to solve the Cartesian problem as part of the 
join enumeration algorithm is to apply a similar strategy to the one that we 
discuss for star-plans. You keep track of "connected" tables and "unconnected" 
tables. During join enumeration, mixed combinations are pruned until the plan 
for the “connected” set of tables was built. Then, we add tables from the 
"unconnected" set - maybe only as left-deep trees (i.e. the size of the inner 
is one). Also, knowing that a set of tables are connected through join 
conditions, will allow further plan pruning based on the presence of join 
predicates. Integration with star-join, and probably other heuristics, would 
require to introduce some filtering/pruning strategies on top of the search 
engine. Just some thoughts… 


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-17 Thread AmplabJenkins
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https://github.com/apache/spark/pull/17286
  
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-17 Thread AmplabJenkins
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https://github.com/apache/spark/pull/17286
  
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-17 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/17286
  
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-17 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/17286
  
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-17 Thread cloud-fan
Github user cloud-fan commented on the issue:

https://github.com/apache/spark/pull/17286
  
retest this please


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-17 Thread AmplabJenkins
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https://github.com/apache/spark/pull/17286
  
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-17 Thread SparkQA
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https://github.com/apache/spark/pull/17286
  
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-17 Thread SparkQA
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https://github.com/apache/spark/pull/17286
  
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-16 Thread cloud-fan
Github user cloud-fan commented on the issue:

https://github.com/apache/spark/pull/17286
  
LGTM except some minor comments


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-16 Thread AmplabJenkins
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-16 Thread SparkQA
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-16 Thread SparkQA
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-16 Thread wzhfy
Github user wzhfy commented on the issue:

https://github.com/apache/spark/pull/17286
  
Co-existing cross joins (join without a condition) and inner joins make the 
reordering procedure cumbersome. On one hand, putting cross join candidates 
into memo is not good in terms of search performance and memory consumption. On 
the other hand, adding cross joins after inner join exploration also has 
problems with multiple unjoinable groups, just putting them at the end of the 
plan is not right.

So I decide to do reordering only for consecutive inner joins, which are 
separated by other plans (including cross joins). For bushy trees, this means 
we will reorder joins within each inner joinable "groups". For left deep trees, 
the `ReorderJoin` rule puts cross joins to the end, so all the previous inner 
joins will be reordered. Since join reorder is a complicated problem, we may 
need several levels of optimization, we can consider `ReorderJoin` as a 
heuristic algorithm.

For common cases when there's no cross join, this algorithm behaves just 
like before.


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-14 Thread AmplabJenkins
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-14 Thread AmplabJenkins
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https://github.com/apache/spark/pull/17286
  
Test FAILed.
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-14 Thread AmplabJenkins
Github user AmplabJenkins commented on the issue:

https://github.com/apache/spark/pull/17286
  
Build finished. Test FAILed.


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-14 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/17286
  
**[Test build #74527 has 
finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/74527/testReport)**
 for PR 17286 at commit 
[`9aee29a`](https://github.com/apache/spark/commit/9aee29a1d50c3a0a1b332f00ca5b41d5f0a2d877).
 * This patch **fails SparkR unit tests**.
 * This patch **does not merge cleanly**.
 * This patch adds no public classes.


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-14 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/17286
  
**[Test build #74528 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/74528/testReport)**
 for PR 17286 at commit 
[`dfc34fc`](https://github.com/apache/spark/commit/dfc34fccae97fa09b382dd215d09173ebf70b2de).


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-14 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/17286
  
**[Test build #74527 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/74527/testReport)**
 for PR 17286 at commit 
[`9aee29a`](https://github.com/apache/spark/commit/9aee29a1d50c3a0a1b332f00ca5b41d5f0a2d877).


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-14 Thread AmplabJenkins
Github user AmplabJenkins commented on the issue:

https://github.com/apache/spark/pull/17286
  
Merged build finished. Test PASSed.


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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-14 Thread AmplabJenkins
Github user AmplabJenkins commented on the issue:

https://github.com/apache/spark/pull/17286
  
Test PASSed.
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...

2017-03-14 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/17286
  
**[Test build #74500 has 
finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/74500/testReport)**
 for PR 17286 at commit 
[`f472c74`](https://github.com/apache/spark/commit/f472c74189f5f54c701876aaa73f7d331e5b814d).
 * This patch passes all tests.
 * This patch merges cleanly.
 * This patch adds the following public classes _(experimental)_:
  * `  case class JoinPlan(`
  * `case class Cost(rows: BigInt, size: BigInt) `


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