[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...
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 ...
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. --- 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 issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...
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 ...
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. --- 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 issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...
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. --- 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 issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...
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 ...
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. --- 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 issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...
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. --- 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
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Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/17286 thanks, merging to master! --- 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 issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...
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 âconnectedâ 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⦠--- 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
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Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/17286 LGTM except some minor comments --- 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
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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. --- 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
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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 ...
Github user AmplabJenkins commented on the issue: https://github.com/apache/spark/pull/17286 Merged build finished. Test PASSed. --- 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 issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...
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[GitHub] spark issue #17286: [SPARK-19915][SQL] Exclude cartesian product candidates ...
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) ` --- 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
