[GitHub] spark issue #22429: [SPARK-25440][SQL] Dumping query execution info to a fil...
Github user MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 Here is a PR introduces `maxFields` parameter to all function involved in creation of truncated strings of spark plans: https://github.com/apache/spark/pull/23159 --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #22429: [SPARK-25440][SQL] Dumping query execution info to a fil...
Github user MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 I am closing the PR since a part of it has been merged in #23018 already, and the rest is coming soon. --- - 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 HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/22429 Ooops i rished to read. Yea but still sounds related but orthogonal. Let's move it to mailing list. That should be the best place to discuss further. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #22429: [SPARK-25440][SQL] Dumping query execution info to a fil...
Github user boy-uber commented on the issue: https://github.com/apache/spark/pull/22429 > @boy-uber, for structured streaming, let's do it out of this PR. I think the actual change of this PR can be small (1.). We can change this API for structured streaming later if needed since this is just an internal private API. Change (2.) can be shared I guess even if we go for structured streaming stuff. Hi @HyukjinKwon thanks for the comment! My original suggestion was not related to structured streaming. It was to support structured logging for Spark plan, for example, get the Spark plan as a json blob, and send it to Spark Listener. This will make it easy to Spark users to write a Spark Listener plugin to get the plan and process the json in their code. Then people could parse and analyze a large number of Spark applications based on their plans. One use case for this is using machine learning to predict resource usage based on the Spark plans. This may not be related to this PR. If you or other people are interested, we could talk offline. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #22429: [SPARK-25440][SQL] Dumping query execution info to a fil...
Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/22429 @boy-uber, for structured streaming, let's do it out of this PR. I think the actual change of this PR can be small (1.). We can change this API for structured streaming later if needed since this is just an internal private API. Change (2.) can be shared I guess even if we go for structured streaming stuff. --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 @HyukjinKwon @cloud-fan Thank you for looking at the PR. So, if I split the PR to 2 PRs: 1. Writing truncated plans to a file 2. Control number of fields in truncated strings. , it would be better for review, right? > I think it's okay to expose that number to toFile. I think this is an internal API, right? Yes, it is. > People could just set whatever number they want I guess. Fix me if I misread. I just had a concern that there are much more places (~10) besides of the `toFile` method where I have to pass some value for `maxFields`. In all such places I have to read a SQL config. --- - 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 HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/22429 I took a super quick pass - the change actually quite looks okay in general to me. --- - 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 HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/22429 @MaxGekk, couple of questions for its implementation from a cursory look. It's the implementation is complicated here: 1. it tries to use writer and avoid to construct the string. I think it's unlikely a single plan causes OOO. I think you can just iterate the plan and write out the trees. 2. This looks introduces `None` concept to indicate no limit which makes this PR hard to read. I think it's okay to expose that number to `toFile`. I think this is an internal API, right? People could just set whatever number they want I guess. Fix me if I misread. If we get rid of those two points, I think the PR size will be drastically small. --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 @cloud-fan > This is hard to review, do you mean we should add maxFields: Option[Int] to all the string related methods? Not to all but only to methods involved to producing textual representation of different plans. Those are `simpleString` and `verboseString` in children of `TreeNode` + `simpleString` of `StructType`. The changes are trivial - I just made them by fixing compilation errors. Maybe I missed somethings but only because it wasn't touched by compiler. Main changes are concentrated in `QueryExecution.scala` where everything begins from the `toFile` method. Other changes are consequences of that. The main idea is to write a OutputStream instead of strings materializations in memory. So, it should allow to avoid limits for string size and OOM which we see sometimes in corner cases. --- - 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/22429 This is hard to review, do you mean we should add `maxFields: Option[Int]` to all the string related methods? --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 @cloud-fan @gatorsmile May I ask you to look at the PR. It stuck for a while by unclear reasons but I believe the proposed method `toFile` could be pretty useful in troubleshooting different issues, and I just don't want to close it so easily. --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 @hvanhovell Could you look at the PR, please. --- - 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 boy-uber commented on the issue: https://github.com/apache/spark/pull/22429 > > @MaxGekk I sent email to spark dev list about structured plan logging, but did not get any response. > > @boy-uber I guess It is better to speak about the feature to @bogdanrdc @hvanhovell @larturus Thanks @MaxGekk for the contact list! I will ping them to gather more thoughts. --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 @gatorsmile @HyukjinKwon @viirya @rednaxelafx Are you ok with the proposed changes or there is something which blocks the PR for now? --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 May I ask you @hvanhovell @zsxwing to review the PR one more time. --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 > @MaxGekk I sent email to spark dev list about structured plan logging, but did not get any response. @boy-uber I guess It is better to speak about the feature to @bogdanrdc @hvanhovell @larturus --- - 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 boy-uber commented on the issue: https://github.com/apache/spark/pull/22429 > > @boy-uber the thing you are suggesting is a pretty big undertaking and beyond the scope of this PR. > > If you are going to add structured plans to the explain output, you probably also want some guarantees about stability over multiple spark versions and you probably also want to be able to reconstruct the plan. Neither is easy. If you want to have this in Spark, then I suggest sending a proposal to the dev list. > > Yeah, that is a larger change and may need more discussion. Your points about adding structured plans like that are great! Let me send a email to the dev list then! Thanks for the suggestion :) @MaxGekk I sent email to spark dev list about structured plan logging, but did not get any response. Thus circle back to discussion here. Do you have interest for work similar to that? If so, we could sync up more offline. --- - 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 boy-uber commented on the issue: https://github.com/apache/spark/pull/22429 > @boy-uber the thing you are suggesting is a pretty big undertaking and beyond the scope of this PR. > > If you are going to add structured plans to the explain output, you probably also want some guarantees about stability over multiple spark versions and you probably also want to be able to reconstruct the plan. Neither is easy. If you want to have this in Spark, then I suggest sending a proposal to the dev list. Yeah, that is a larger change and may need more discussion. Your points about adding structured plans like that are great! Let me send a email to the dev list then! Thanks for the suggestion :) --- - 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 hvanhovell commented on the issue: https://github.com/apache/spark/pull/22429 @boy-uber the thing you are suggesting is a pretty big undertaking and beyond the scope of this PR. If you are going to add structured plans to the explain output, you probably also want some guarantees about stability over multiple spark versions and you probably also want to be able to reconstruct the plan. Neither is easy. If you want to have this in Spark, then I suggest sending a proposal to the dev list. --- - 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 boy-uber commented on the issue: https://github.com/apache/spark/pull/22429 Great to see the code here to capture more information from the plan and save to file. We have similar needs with our Spark applications as well. Adding my two cents: 1. Anyone feel the need to log the spark plan as a json or other structured representation? Current text based logging for spark plan is good for human, but hard to be processed by code/tool. 2. Could we generalize the solution a little bit? for example, writing the logical/physical plan json representation (or similar tree structure) to Spark listener, so people could write their own plugin to either write to file, or write to database, or write to kafka, etc. --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 @zsxwing Please, have a look at the PR one more time. --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 @gatorsmile @zsxwing @hvanhovell @viirya @rednaxelafx @HyukjinKwon Please, take a look at the PR. --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 As far as I know, @hvanhovell, you would prefer replacing `Option[Int]` by just `Int` in `simpleString` and other similar places. I can do that but I have to read the config parameter in all those places where I pass `None` at the moment. I have counted ~ 26 places. @zsxwing Do you also prefer this approach? --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 > Could you also try to remove the default value? I have removed the default value `None` but still keep type as `Option[Int]`. @zsxwing Is it ok? > org.apache.spark.util.Utils.truncatedString seems in a wrong project. ... Could you move it to the catalyst project. Moved to `catalyst`. > In addition, it would be great that you can change it to a SQL conf so that we can modify this config dynamically. Do you mean moving the `spark.debug.maxToStringFields` to `SQLConf` or adding another SQL config like `spark.sql.maxFieldsInTruncatedString`? --- - 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 zsxwing commented on the issue: https://github.com/apache/spark/pull/22429 @MaxGekk Make sense. Could you also try to remove the default value? --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 > Can we change `maxFields: Option[Int]` to `maxFields: Int` so that the caller will never forget to pass it in and it should either get it from some place or use the default value. @zsxwing Sure, but only replacing `Option[Int]` by `Int` cannot guarantee that. Need to remove default value to force a caller to pass a value to `simpleString()` --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 @gatorsmile @rednaxelafx @HyukjinKwon @viirya @hvanhovell Could you review the PR, please. --- - 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 MaxGekk commented on the issue: https://github.com/apache/spark/pull/22429 @hvanhovell May I ask you to look at this one more time. --- - 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 #22429: [SPARK-25440][SQL] Dumping query execution info to a fil...
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