[GitHub] spark pull request: [SPARK-14098][SQL] Generate Java code that get...
Github user kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-220422809 @davies thank you for your response. Since @rxin categorized this into 2.1, I understand it should be review for 2.1. When 2.0 is out, I will ping you for the review. I would appreciate it if you would recommend other possible reviewers when you have time. --- 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-14098][SQL] Generate Java code that get...
Github user davies commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-220056332 To be honest, Right now is too late to review and merge this into 2.0. I'm busy with other important things on 2.0, does not have enough bandwidth to review it. You could ask other people to look into the design in details. --- 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-14098][SQL] Generate Java code that get...
Github user kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-220019065 ping @davies --- 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-14098][SQL] Generate Java code that get...
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[GitHub] spark pull request: [SPARK-14098][SQL] Generate Java code that get...
Github user kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-217775281 @davies As you suggested, I moved most of the implmentation from ```WholeStageCodegenExec``` to ```InMemoryTableScanExec```. Now, the number of changed lines in ```WholeStageCodegenExec.scala``` is about 30 lines. Since it is hard to pass an instance of ```InMemoryTableScanExec``` to ```InputAdaptor```, I newly introduced ```object InMemoryTableScanExec```. Could you please review this PR? --- 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 kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-217241905 I missed something. While I assumed that I would newly declare a singleton object ```InMemoryTableScanExec``` and move 2. and 3. into new methods in the object. As you pointed out, it can be done in a case class. For example, I will move [lines 263-296](https://github.com/apache/spark/pull/11956/files#diff-28cb12941b992ff680c277c651b59aa0R263) and [lines 374-403](https://github.com/apache/spark/pull/11956/files#diff-28cb12941b992ff680c277c651b59aa0R374) into each of two methods in the ```InMemoryTableScanExec``` and then put method calls into the original places in ``WholeStageCodegenExec```. Is this what you want to do? --- 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 davies commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-217074291 InMemoryTableScanExec is a case class, not singleton, why can we not implement these there? --- 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 kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-217047879 @davies, thank you for your comment. Based on your previous comment, [this commit](https://github.com/apache/spark/pull/11956/commits/d2161d13dab9871ce0e325fcc3934c2f4f5eca13) already moved some stuff of the implementation to ```InMemoryTableScanExec```. Now, ```WholeStageCodegenExec``` does only the following three features. 1. decide whether code for columnar storage should be generated 2. generate ```processRow()``` and ```processBatch``` 3. generate runtime conditional-if statement whether ```processRow()``` or ```processBatch``` called Do you mean these three features should be moved to ```InMemoryTableScanExec```? While I could do, my understanding is that these features would be implemented by methods in a singleton ```InMemoryTableScanExec```. Do you have any other good ideas to implement these features in ```InMemoryTableScanExec```? --- 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 davies commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-216953038 In high level, I think most of the implementation should be done in InMemoryTableScanExec, not in WholeStageCodegenExec. --- 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 kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-215976979 @davies for ease of review, it would be good to split this PR into two. One is only for float and double primitive types. The other is for other primitive types. The first one focuses on PassThrough compression type in Dataframe cache. The latter focuses on other compression types in Dataframe cache. I estimated that the size of each of PR is about 900 lines. Would it be possible to let us know If there are any issues? --- 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 kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-215696918 @davies I love your idea to use Apache Arrow or other in-memory format instead of ```Array[Byte]``` for DataFrame cache. That is what I want to create a JIRA entry in near future. This idea is related to Part 1 (get data from columnar storage for DataFrame cache under ```org.apache.spark.sql.execution.columnar```) in this PR. Even if we use any in-memory format, an interface to code generation would be ColumnVector. As you can see, we already succeeded to wrap ```Array[Byte]``` and Parquet representation by using methods such as ```getInt()``` in ```ColumnVector```. In this PR, can we target Part 2 (codegen under```org.apache.spark.sql.execution```) of this PR for 2.0 at least? This is because Part 2 could accept any in-memory representation thru ```ColumnVector```. Part 2 is very small (less than 200 lines) after dropping code for Part 1. Thus, it is easy to review. --- 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 davies commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-215530899 @kiszk Can we target this for 2.1? We may switch to use Apache Arrow or other in-memory representation instead of current one. --- 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 kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-215524446 We can shrink the size of this PR (reducing the number of lines from 1800 to 700) by dropping test suites (1450 lines) and a benchmark program (250 lines). Is it better for ease of your review? --- 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 kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-215365815 ping @davies --- 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 kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-214593726 @rxin, would it be possible to review this PR, too? Especially, for decompression part that you originally wrote. --- 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 kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-213417886 @davies, thank you for your great suggestion. Now, I simplified changes in ```WholeStageCodeGen.scala' by moving a logic regarding ```CachedBatch``` to other files. The total number of increased lines is reduced from 115 to 95.The generated code is also simplified since variables regarding ```CachedBatch``` are moved away. The total number of generated code is also reduced from 150 to 139. I updated generated code and performance result in this PR. --- 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 kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-213301701 I know this is huge. Sorry for that. There are three reasons. One is to include benchmark. The other is include test cases. The last one is to newly introduce decompress() method for each of compression algorithm. Is it better to split this into two parts: decompress() and code generation? Also, I will try to reduce changes into WholeStageCodegen by moving some of them into other files such as InMemoryTableScan and GenerateColumnAccessor. --- 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 davies commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-213299060 This PR is huge, I may not have enough time to review this. Just saw that there is lots of changes in WholeStageCodegen, is it possible to avoid most of them (simplify the logic or move it to InMemoryTableScan)? --- 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 kiszk commented on the pull request: https://github.com/apache/spark/pull/11956#issuecomment-212971005 @davies , would it be possible to review this PR? --- 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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