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[SPARK-13979][Core] Killed executor is re spawned without AWS key… #14601
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…s in standalone spark cluster
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Jenkins test this please |
| } | ||
| // Copy any "spark.hadoop.foo=bar" system properties into conf as "foo=bar" | ||
| conf.getAll.foreach { case (key, value) => | ||
| if (key.startsWith("spark.hadoop.")) { |
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the comment above does not apply for the whole loop anymore and should be moved to this if statement
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done.
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Minor, the title should be [CORE] instead of [SPARK CORE] |
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Also, will this also fix the scenario where the user has provided the properties programmatically ? |
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@lresende yes this fix works for the the scenario where the user has provided the properties programmatically like for swift:- |
| } | ||
| // Copy any "fs.swift2d.foo=bar" properties into conf as "fs.swift2d.foo=bar" | ||
| else if (key.startsWith("fs.swift2d")){ | ||
| hadoopConf.set(key, value) |
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What's swift2d? It's not the swift client in hadoop-openstack, which is fs.swift
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swift2d is used when u are using Stocator --> https://github.com/SparkTC/stocator. now I have updated for hadoop-openstack also
have updated for hadoop-openstack package properties
added comment with jira number
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I'd like to propose that the list of filesystem properties to propagate is actually defined as a list in a spark property, default could be "fs.s3a, fs.s3n, fs.s3, fs.swift, fs.wasb". This will allow people to extend it (google GCFS, Allyun OSS HADOOP-12756, etc, without having to patch spark or wait for a new release. And they get the option to turn off the feature whatsoever. By using the full fs.prefix you could also let people add other properties to carry over. One thing I'm confused by though: why do spawned executors get the properties, but not respawned ones? |
| // Copy any "fs.s3.foo=bar" or "fs.s3a.foo=bar" or "fs.s3n.foo=bar" properties into conf | ||
| else if (key.startsWith("fs.s3")){ | ||
| hadoopConf.set(key, value) | ||
| } |
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s3 is the AWS EMR filesystem, but an obsolete one on ASF Hadoop. I would recommend the list of
s3, s3n, s3a, swift, adl, wasb, oss, gs
(edited 10/oct, set list in sync with what I believe is current set)
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Actually, I would copy everything under fs.s3a, fs.s3, etc. Why? there's a lot more than passwords: for s3a we include: proxy info and passwords, a list of alternate s3 auth mechanisms (e.g. declaring using IAM), etc, etc.
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@steveloughran can u help me with some default setting for adl, wasb, oss, gs to test or just syntax for them so that i can decide on filter conditions
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Could an automated test be done here. propagation can be tested with a a function run on the
Seq("s3n", s3a.aws", ...).parallelize.map { name -> (check for fs.s3a properties) or fail } |
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@agsachin Are you planning to address these updates on this PR ? It would be good to have this as part of Spark as it affects multiple usage scenarios in cloud platforms and other cases as well. |
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(gentle ping @agsachin) |
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@lresende @steveloughran @HyukjinKwon can we go ahead with key.startsWith("fs."). so that we don't need to check so many conditions. |
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spark.hadoop.fs.* would work. The (not yet shipped in ASF code) Azure Data Lake FS has, for reasons I don't know and have only just noticed, adopted "dfs.adl" as their prefix. That's going to be fixed before it gets out the door, so fs.* will work there too. |
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@steveloughran I have updated the pull request to fs.* |
update issue 2 is fixed |
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@agsachin Are you still working on this? And if it is so, would you please update the description and provide some snapshot to demo the behaviors before & after the changes? It would also be great if some test cases could be provided(I hope it won't be too hard). |
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add to whitelist |
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test this please |
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Testing should not be too hard. Here's my untested attempt val sconf = new SparkConf(false)
sconf.set("fs.example.value", "true")
val conf = new Configuration(false)
new SparkHadoopUtil().appendS3AndSparkHadoopConfigurations(sconf, conf)
assert(conf.getBoolean("fs.example.value", false)) |
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gentle ping @agsachin. |
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Thanks @jiangxb2987 will add this test case by tomorrow and will be update the pr with results |
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I know this hasn't been updated, but it is still important. I can take it on if all it needs is a test case |
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@steveloughran Please feel free to reopen this PR. Thanks! |
## What changes were proposed in this pull request? This PR proposes to close stale PRs, mostly the same instances with apache#18017 Closes apache#14085 - [SPARK-16408][SQL] SparkSQL Added file get Exception: is a directory … Closes apache#14239 - [SPARK-16593] [CORE] [WIP] Provide a pre-fetch mechanism to accelerate shuffle stage. Closes apache#14567 - [SPARK-16992][PYSPARK] Python Pep8 formatting and import reorganisation Closes apache#14579 - [SPARK-16921][PYSPARK] RDD/DataFrame persist()/cache() should return Python context managers Closes apache#14601 - [SPARK-13979][Core] Killed executor is re spawned without AWS key… Closes apache#14830 - [SPARK-16992][PYSPARK][DOCS] import sort and autopep8 on Pyspark examples Closes apache#14963 - [SPARK-16992][PYSPARK] Virtualenv for Pylint and pep8 in lint-python Closes apache#15227 - [SPARK-17655][SQL]Remove unused variables declarations and definations in a WholeStageCodeGened stage Closes apache#15240 - [SPARK-17556] [CORE] [SQL] Executor side broadcast for broadcast joins Closes apache#15405 - [SPARK-15917][CORE] Added support for number of executors in Standalone [WIP] Closes apache#16099 - [SPARK-18665][SQL] set statement state to "ERROR" after user cancel job Closes apache#16445 - [SPARK-19043][SQL]Make SparkSQLSessionManager more configurable Closes apache#16618 - [SPARK-14409][ML][WIP] Add RankingEvaluator Closes apache#16766 - [SPARK-19426][SQL] Custom coalesce for Dataset Closes apache#16832 - [SPARK-19490][SQL] ignore case sensitivity when filtering hive partition columns Closes apache#17052 - [SPARK-19690][SS] Join a streaming DataFrame with a batch DataFrame which has an aggregation may not work Closes apache#17267 - [SPARK-19926][PYSPARK] Make pyspark exception more user-friendly Closes apache#17371 - [SPARK-19903][PYSPARK][SS] window operator miss the `watermark` metadata of time column Closes apache#17401 - [SPARK-18364][YARN] Expose metrics for YarnShuffleService Closes apache#17519 - [SPARK-15352][Doc] follow-up: add configuration docs for topology-aware block replication Closes apache#17530 - [SPARK-5158] Access kerberized HDFS from Spark standalone Closes apache#17854 - [SPARK-20564][Deploy] Reduce massive executor failures when executor count is large (>2000) Closes apache#17979 - [SPARK-19320][MESOS][WIP]allow specifying a hard limit on number of gpus required in each spark executor when running on mesos Closes apache#18127 - [SPARK-6628][SQL][Branch-2.1] Fix ClassCastException when executing sql statement 'insert into' on hbase table Closes apache#18236 - [SPARK-21015] Check field name is not null and empty in GenericRowWit… Closes apache#18269 - [SPARK-21056][SQL] Use at most one spark job to list files in InMemoryFileIndex Closes apache#18328 - [SPARK-21121][SQL] Support changing storage level via the spark.sql.inMemoryColumnarStorage.level variable Closes apache#18354 - [SPARK-18016][SQL][CATALYST][BRANCH-2.1] Code Generation: Constant Pool Limit - Class Splitting Closes apache#18383 - [SPARK-21167][SS] Set kafka clientId while fetch messages Closes apache#18414 - [SPARK-21169] [core] Make sure to update application status to RUNNING if executors are accepted and RUNNING after recovery Closes apache#18432 - resolve com.esotericsoftware.kryo.KryoException Closes apache#18490 - [SPARK-21269][Core][WIP] Fix FetchFailedException when enable maxReqSizeShuffleToMem and KryoSerializer Closes apache#18585 - SPARK-21359 Closes apache#18609 - Spark SQL merge small files to big files Update InsertIntoHiveTable.scala Added: Closes apache#18308 - [SPARK-21099][Spark Core] INFO Log Message Using Incorrect Executor I… Closes apache#18599 - [SPARK-21372] spark writes one log file even I set the number of spark_rotate_log to 0 Closes apache#18619 - [SPARK-21397][BUILD]Maven shade plugin adding dependency-reduced-pom.xml to … Closes apache#18667 - Fix the simpleString used in error messages Closes apache#18782 - Branch 2.1 Added: Closes apache#17694 - [SPARK-12717][PYSPARK] Resolving race condition with pyspark broadcasts when using multiple threads Added: Closes apache#16456 - [SPARK-18994] clean up the local directories for application in future by annother thread Closes apache#18683 - [SPARK-21474][CORE] Make number of parallel fetches from a reducer configurable Closes apache#18690 - [SPARK-21334][CORE] Add metrics reporting service to External Shuffle Server Added: Closes apache#18827 - Merge pull request 1 from apache/master ## How was this patch tested? N/A Author: hyukjinkwon <[email protected]> Closes apache#18780 from HyukjinKwon/close-prs.
What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
Summery we need to make two changes
How was this patch tested?
This patch was manually tested on local machine in standalone cluster mode.
To simulate the case of executor failure. We manually killed the executor then master started new executor with updated config params.
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
no
…s in standalone spark cluster