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[GitHub] [spark] ulysses-you opened a new pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file

ulysses-you opened a new pull request #32184:
URL: https://github.com/apache/spark/pull/32184


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   Use hadoop FileSystem instead of FileInputStream.
   
   ### Why are the changes needed?
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   Make `spark.scheduler.allocation.file` suport remote file. When using Spark as a server (e.g. SparkThriftServer), it's hard for user to specify a local path as the scheduler pool.
   
   
   ### Does this PR introduce _any_ user-facing change?
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   Yes, a minor feature.
   
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   Pass `core/src/test/scala/org/apache/spark/scheduler/PoolSuite.scala` and manul test
   After add config `spark.scheduler.allocation.file=hdfs:///tmp/fairscheduler.xml`. We intrudoce the configed pool.
   ![pool1](https://user-images.githubusercontent.com/12025282/114810037-df065700-9ddd-11eb-8d7a-54b59a07ee7b.jpg)
   


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[GitHub] [spark] SparkQA commented on pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file using hadoop api

Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/32184#issuecomment-820900295


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[GitHub] [spark] SparkQA commented on pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file

Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/32184#issuecomment-820087668


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[GitHub] [spark] dongjoon-hyun closed pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool files

Posted by GitBox <gi...@apache.org>.
dongjoon-hyun closed pull request #32184:
URL: https://github.com/apache/spark/pull/32184


   


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[GitHub] [spark] HyukjinKwon commented on a change in pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool files

Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #32184:
URL: https://github.com/apache/spark/pull/32184#discussion_r692191737



##########
File path: docs/job-scheduling.md
##########
@@ -252,10 +252,11 @@ properties:
 
 The pool properties can be set by creating an XML file, similar to `conf/fairscheduler.xml.template`,
 and either putting a file named `fairscheduler.xml` on the classpath, or setting `spark.scheduler.allocation.file` property in your
-[SparkConf](configuration.html#spark-properties).
+[SparkConf](configuration.html#spark-properties). The file path can either be a local file path or HDFS file path.

Review comment:
       Actually, this line isn't completely true. It can be a local file path only when `fs.default.scheme` is `file:///` which usually isn't in production.
   
   So, if users from old Spark versions use a path like `/path/to/file`, the files will be written into HDFS after the upgrade.
   
   Can we at least update the migration guide? We should also mention that it respects Hadoop properties now.




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[GitHub] [spark] ulysses-you commented on a change in pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file using hadoop api

Posted by GitBox <gi...@apache.org>.
ulysses-you commented on a change in pull request #32184:
URL: https://github.com/apache/spark/pull/32184#discussion_r614534549



##########
File path: core/src/test/scala/org/apache/spark/scheduler/PoolSuite.scala
##########
@@ -332,12 +337,36 @@ class PoolSuite extends SparkFunSuite with LocalSparkContext {
     sc = new SparkContext(LOCAL, APP_NAME, conf)
 
     val rootPool = new Pool("", SchedulingMode.FAIR, 0, 0)
-    val schedulableBuilder = new FairSchedulableBuilder(rootPool, sc.conf)
+    val schedulableBuilder = new FairSchedulableBuilder(rootPool, sc)
     intercept[FileNotFoundException] {
       schedulableBuilder.buildPools()
     }
   }
 
+  test("SPARK-35083: Support remote scheduler pool file") {
+    val hadoopVersion = VersionInfo.getVersion.split("\\.")
+    // HttpFileSystem supported since hadoop 2.9
+    assume(hadoopVersion.head.toInt >= 3 ||
+      (hadoopVersion.head.toInt == 2 && hadoopVersion(1).toInt >= 9))

Review comment:
       This check is to avoid `java.io.IOException: No FileSystem for scheme: http` if we use hadoop 2.7 which Spark still supports.




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[GitHub] [spark] dongjoon-hyun commented on a change in pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool files

Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on a change in pull request #32184:
URL: https://github.com/apache/spark/pull/32184#discussion_r692307824



##########
File path: docs/job-scheduling.md
##########
@@ -252,10 +252,11 @@ properties:
 
 The pool properties can be set by creating an XML file, similar to `conf/fairscheduler.xml.template`,
 and either putting a file named `fairscheduler.xml` on the classpath, or setting `spark.scheduler.allocation.file` property in your
-[SparkConf](configuration.html#spark-properties).
+[SparkConf](configuration.html#spark-properties). The file path can either be a local file path or HDFS file path.

Review comment:
       +1 for @HyukjinKwon 's advice.




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[GitHub] [spark] dongjoon-hyun commented on a change in pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file using hadoop api

Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on a change in pull request #32184:
URL: https://github.com/apache/spark/pull/32184#discussion_r614115181



##########
File path: core/src/main/scala/org/apache/spark/scheduler/SchedulableBuilder.scala
##########
@@ -74,7 +76,8 @@ private[spark] class FairSchedulableBuilder(val rootPool: Pool, conf: SparkConf)
     var fileData: Option[(InputStream, String)] = None
     try {
       fileData = schedulerAllocFile.map { f =>
-        val fis = new FileInputStream(f)
+        val filePath = new Path(f)
+        val fis = filePath.getFileSystem(sc.hadoopConfiguration).open(filePath)

Review comment:
       This code can do many things. Please see my above comment. (https://github.com/apache/spark/pull/32184#issuecomment-820459844)




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[GitHub] [spark] ulysses-you commented on pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file

Posted by GitBox <gi...@apache.org>.
ulysses-you commented on pull request #32184:
URL: https://github.com/apache/spark/pull/32184#issuecomment-820031692


   Do you have time to take a look if you don't mind ? @dongjoon-hyun @srowen @Ngone51 


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[GitHub] [spark] ulysses-you commented on pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file using hadoop api

Posted by GitBox <gi...@apache.org>.
ulysses-you commented on pull request #32184:
URL: https://github.com/apache/spark/pull/32184#issuecomment-820840238


   @dongjoon-hyun Thank you very much for the explanation. I have never used the http filesystem before so that not realized it was supported by hadoop FileSystem (seems form hadoop2.9 [HADOOP-1438](https://issues.apache.org/jira/browse/HADOOP-14383) which is an advance version for us).
   
   I will check it and add some test.


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[GitHub] [spark] Ngone51 commented on a change in pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file

Posted by GitBox <gi...@apache.org>.
Ngone51 commented on a change in pull request #32184:
URL: https://github.com/apache/spark/pull/32184#discussion_r613778383



##########
File path: docs/job-scheduling.md
##########
@@ -256,6 +256,7 @@ and either putting a file named `fairscheduler.xml` on the classpath, or setting
 
 {% highlight scala %}
 conf.set("spark.scheduler.allocation.file", "/path/to/file")
+conf.set("spark.scheduler.allocation.file", "hdfs:///path/to/file")

Review comment:
       I think HDFS also supports reading the local file. Could you mention it in the above document? e.g., "The file path can either be a local file path or HDFS file path."




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[GitHub] [spark] SparkQA commented on pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file

Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/32184#issuecomment-820151183


   **[Test build #137394 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/137394/testReport)** for PR 32184 at commit [`8bd973d`](https://github.com/apache/spark/commit/8bd973dc8df11e24c2ae2e8008baf675c96707e6).
    * This patch passes all tests.
    * This patch merges cleanly.
    * This patch adds no public classes.


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[GitHub] [spark] dongjoon-hyun commented on pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file using hadoop api

Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on pull request #32184:
URL: https://github.com/apache/spark/pull/32184#issuecomment-820459844


   > @dongjoon-hyun looked into that PR, it provided a Http server. This PR aims to support the remote file using HDFS api, seems we can not add a useful test.
   > 
   > Update the pr title to make it clear.
   
   
   Hi, @ulysses-you . It seems that you are underestimating your PR's contribution. :)
   Hadoop API is an abstraction layer to support various file systems like the following.
   
   ```scala
   scala> new org.apache.hadoop.fs.Path("file:///tmp/README.md").getFileSystem(sc.hadoopConfiguration)
   res0: org.apache.hadoop.fs.FileSystem = org.apache.hadoop.hive.ql.io.ProxyLocalFileSystem@1def2d16
   
   scala> new org.apache.hadoop.fs.Path("https://spark.apache.org/index.html").getFileSystem(sc.hadoopConfiguration)
   res1: org.apache.hadoop.fs.FileSystem = org.apache.hadoop.fs.http.HttpsFileSystem@4058b398
   
   scala> new org.apache.hadoop.fs.Path("s3a://dongjoon/README.md").getFileSystem(sc.hadoopConfiguration)
   res2: org.apache.hadoop.fs.FileSystem = S3AFileSystem{uri=s3a://dongjoon,...
   ```
   
   Have you try to put your pool file on other file systems, HTTP Webserver or S3 (or S3-compatible MinIO)? Do you mean it doesn't work for you, @ulysses-you ?


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[GitHub] [spark] ulysses-you commented on a change in pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool files

Posted by GitBox <gi...@apache.org>.
ulysses-you commented on a change in pull request #32184:
URL: https://github.com/apache/spark/pull/32184#discussion_r692598890



##########
File path: docs/job-scheduling.md
##########
@@ -252,10 +252,11 @@ properties:
 
 The pool properties can be set by creating an XML file, similar to `conf/fairscheduler.xml.template`,
 and either putting a file named `fairscheduler.xml` on the classpath, or setting `spark.scheduler.allocation.file` property in your
-[SparkConf](configuration.html#spark-properties).
+[SparkConf](configuration.html#spark-properties). The file path can either be a local file path or HDFS file path.

Review comment:
       @HyukjinKwon sorry, not sure I get your point.
   
   > So, if users from old Spark versions use a path like /path/to/file, the files will be written into HDFS after the upgrade.
   
   Why we need to write files into HDFS ? This PR is to support read remote file as the schedule pool. I think there is no behavior change but just a new feature.
   




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[GitHub] [spark] ulysses-you edited a comment on pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file using hadoop api

Posted by GitBox <gi...@apache.org>.
ulysses-you edited a comment on pull request #32184:
URL: https://github.com/apache/spark/pull/32184#issuecomment-820173682


   @dongjoon-hyun looked into that PR, it provided a Http server. This PR aims to support the remote file using HDFS api, seems we can not add a useful test.
   
   Update the pr title to make it clear.


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    * This patch merges cleanly.
    * This patch adds no public classes.


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[GitHub] [spark] HyukjinKwon commented on a change in pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool files

Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #32184:
URL: https://github.com/apache/spark/pull/32184#discussion_r692624659



##########
File path: docs/job-scheduling.md
##########
@@ -252,10 +252,11 @@ properties:
 
 The pool properties can be set by creating an XML file, similar to `conf/fairscheduler.xml.template`,
 and either putting a file named `fairscheduler.xml` on the classpath, or setting `spark.scheduler.allocation.file` property in your
-[SparkConf](configuration.html#spark-properties).
+[SparkConf](configuration.html#spark-properties). The file path can either be a local file path or HDFS file path.

Review comment:
       thanks man!




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[GitHub] [spark] yaooqinn commented on pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool file

Posted by GitBox <gi...@apache.org>.
yaooqinn commented on pull request #32184:
URL: https://github.com/apache/spark/pull/32184#issuecomment-820092327


   looks nice, and good to have it tested per @dongjoon-hyun's suggestion


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[GitHub] [spark] ulysses-you commented on pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool files

Posted by GitBox <gi...@apache.org>.
ulysses-you commented on pull request #32184:
URL: https://github.com/apache/spark/pull/32184#issuecomment-820996503


   thanks for merging !


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[GitHub] [spark] ulysses-you commented on a change in pull request #32184: [SPARK-35083][CORE] Support remote scheduler pool files

Posted by GitBox <gi...@apache.org>.
ulysses-you commented on a change in pull request #32184:
URL: https://github.com/apache/spark/pull/32184#discussion_r692600086



##########
File path: docs/job-scheduling.md
##########
@@ -252,10 +252,11 @@ properties:
 
 The pool properties can be set by creating an XML file, similar to `conf/fairscheduler.xml.template`,
 and either putting a file named `fairscheduler.xml` on the classpath, or setting `spark.scheduler.allocation.file` property in your
-[SparkConf](configuration.html#spark-properties).
+[SparkConf](configuration.html#spark-properties). The file path can either be a local file path or HDFS file path.

Review comment:
       I see , if user specify a path `/path/to/file` with no scheme then after this PR, Spark will load it from HDFS instead of local. That worth a migration guide , thank you point out this ! @HyukjinKwon @dongjoon-hyun 




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Posted by GitBox <gi...@apache.org>.
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   @dongjoon-hyun looked into that PR, it provided a Http server. This PR aims to support the remote file using HDFS api, seems we can not add a useful test.


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