[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user dongjoon-hyun commented on the issue: https://github.com/apache/spark/pull/13775 Hmm. It seems `Merge remote-tracking branch` makes rebasing confused. Let me think how to compare this. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user dongjoon-hyun commented on the issue: https://github.com/apache/spark/pull/13775 Thank you! First, I'll try to rebase and run with my `OrcReadBenchmark` (which is similar with ParquetReadBenchmark). --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 @dongjoon-hyun No problem. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user dongjoon-hyun commented on the issue: https://github.com/apache/spark/pull/13775 Otherwise, may I implement this way in my PR as a Viirya's approach? --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 @dongjoon-hyun Sure. Do you need any help? --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user dongjoon-hyun commented on the issue: https://github.com/apache/spark/pull/13775 @viirya . If possible, I'd like to benchmark this PR in my laptop. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 @rxin @davies @hvanhovell @yhuai @tejasapatil @zjffdu @dafrista I've address review comments and add tests. Please help review this if you can. Thanks. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 By supporting Spark's ColumnarBatch, the benchmarks show this vectorized Orc reader can boost 2 to 3x improvement. I will continue to add more tests. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 retest this please. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 > 1. Can we just convert Hive's vector format into our own column batch, to avoid turning the data into rows? I'd imagine you will get a bigger speedup here. @rxin You are right. After converting Hive's column vectors into Spark's column batch, the performance is largely improved. I've posted the newer benchmark in the pr description. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 @tejasapatil Thanks for the review comment! I will update this later. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 I agree that from a maintenance standpoint forking the classes is bad. But if we really want to have the one in Spark, I would like to help too. :) --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user rxin commented on the issue: https://github.com/apache/spark/pull/13775 If we do want to maintain one in Spark, we should probably start by adding Presto's. Data formats don't change super frequently, so I think we would be able to maintain it, especially when a large company like Facebook has resources devoted to making it work :) --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user tejasapatil commented on the issue: https://github.com/apache/spark/pull/13775 Earlier this year I had spent some time trying out Presto's ORC reader with Spark. In standalone benchmark, Presto's ORC reader is 3x faster than the one in Hive. My experimental setup was to add a CLI around ORC reader code in both hive and presto. It would read a file from local disk and deserialize all the columns. With that promising result, I tried hooking Presto reader with Spark. Presto has its own notion of "page" to manage memory and "slice" for Unsafe access to data. When I integrated it with Spark, I had to add a shim to convert Spark objects to corresponding Presto objects. This hurts performance. Then I decided to fork few classes from Presto to make it directly work with Spark's internal data representations (eg. `UTF8String`). My final numbers (for end to end runs of Spark jobs) were ranging from no gains to 2x improvement. Note that there were things Presto's reader supports (namely vectorization and predicate pushdown) which I had not integrated as that would have demanded more forking. The measurements were over queries which ran over large table, read all the rows and wrote those as-is to another table. Having done all these things, my personal take is that forking classes is bad from a maintenance standpoint. Presto's ORC reader is tightly coupled with the engines' internal constructs and refactoring it to make it generic is non-trivial work. We can think about having a native ORC reader in Spark (just like Presto does) which would be super performant but the downside is that one has to be sync with all upstream changes to the file format as it evolves. cc @rxin (I recall you were also interested in this at some point) --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user davies commented on the issue: https://github.com/apache/spark/pull/13775 @viirya Have you tried the ORC reader in presto? I guess that one is more efficient than the one in Hive. But not sure how hard will be to make it work with Spark SQL (column batch). --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 @rxin Thanks for looking at this! 1. My initial investigation when implementing this PR is looking at this direction too. Because this is waiting for a while, I can only remember that converting Hive vector format to column batch is not trivial. But I will look at this in second try. 2. Yeah, I will try to add more tests. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user rxin commented on the issue: https://github.com/apache/spark/pull/13775 This is an interesting pull request (very similar to the Parquet approach). Two high level comments: 1. Can we just convert Hive's vector format into our own column batch, to avoid turning the data into rows? I'd imagine you will get a bigger speedup here. 2. We need more tests. This patch has almost no tests. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 retest this please. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 ping @rxin @yhuai @liancheng @hvanhovell @cloud-fan Can you take a look? This is waiting for review for a while. Thanks! --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 ping @yhuai @liancheng @hvanhovell @cloud-fan again... --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 ping @yhuai @liancheng @hvanhovell @cloud-fan Can you take a look at this? Thanks. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 ping @yhuai Any chance you can review this? Thank you. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 @yhuai I ran another benchmark for the scan operation. The results are updated in the pr description. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue:
https://github.com/apache/spark/pull/13775
@yhuai You mean just using `sql("SELECT * FROM t").count()`?
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
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[GitHub] spark issue #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user yhuai commented on the issue: https://github.com/apache/spark/pull/13775 for the benchmark, how about we just test the scan operation? --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 ping @hvanhovell @rxin @liancheng @yhuai Could you review this now? Thanks. --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
Github user viirya commented on the issue: https://github.com/apache/spark/pull/13775 also cc @liancheng @yhuai --- 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 #13775: [SPARK-16060][SQL] Vectorized Orc reader
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