[GitHub] [spark] HyukjinKwon commented on issue #23946: [SPARK-26860][PySpark] [SparkR] Fix for RangeBetween and RowsBetween docs to be in sync with spark documentation

2019-03-07 Thread GitBox
HyukjinKwon commented on issue #23946: [SPARK-26860][PySpark] [SparkR] Fix for 
RangeBetween and RowsBetween docs to be in sync with spark documentation
URL: https://github.com/apache/spark/pull/23946#issuecomment-470839794
 
 
   If the docs are consistent, should be good to go. Let me compare them later 
if no one reviews in few days.


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[GitHub] [spark] HyukjinKwon commented on a change in pull request #23946: [SPARK-26860][PySpark] [SparkR] Fix for RangeBetween and RowsBetween docs to be in sync with spark documentation

2019-03-07 Thread GitBox
HyukjinKwon commented on a change in pull request #23946: 
[SPARK-26860][PySpark] [SparkR] Fix for RangeBetween and RowsBetween docs to be 
in sync with spark documentation
URL: https://github.com/apache/spark/pull/23946#discussion_r263692570
 
 

 ##
 File path: python/pyspark/sql/window.py
 ##
 @@ -97,6 +97,33 @@ def rowsBetween(start, end):
 and ``Window.currentRow`` to specify special boundary values, rather 
than using integral
 values directly.
 
+A row based boundary is based on the position of the row within the 
partition.
+An offset indicates the number of rows above or below the current row, 
the frame for the
+current row starts or ends. For instance, given a row based sliding 
frame with a lower bound
+offset of -1 and a upper bound offset of +2. The frame for row with 
index 5 would range from
+index 4 to index 6.
+
+>>> from pyspark.sql import Window
+>>> from pyspark.sql import functions as func
+>>> from pyspark.sql import SQLContext
+>>> sc = SparkContext.getOrCreate()
+>>> sqlContext = SQLContext(sc)
+>>> tup = [(1, "a"), (1, "a"), (2, "a"), (1, "b"), (2, "b"), (3, "b")]
+>>> df = sqlContext.createDataFrame(tup, ["id", "category"])
+>>> window = 
Window.partitionBy("category").orderBy("id").rowsBetween(Window.currentRow, 1)
+>>> df.withColumn("sum", func.sum("id").over(window)).show()
++---++---+
+| id|category|sum|
++---++---+
+|  1|   b|  3|
+|  2|   b|  5|
+|  3|   b|  3|
+|  1|   a|  2|
+|  1|   a|  3|
+|  2|   a|  2|
++---++---+
+
 
 Review comment:
   Nope, it's not necessary. `optionflags=doctest.NORMALIZE_WHITESPACE` is 
needed just to make the doc prettier (by getting rid of ``).
   
   ```python
   (failure_count, test_count) = doctest.testmod(
   pyspark.sql.window, 
   ```
   
   is just to make the module path pretty. In console, it possible to show the 
module path like `__main__.bla.bla`. In this way, it shows up like 
`pyspark.sql.window.bla.bla`. Not a big deal a t all. 


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[GitHub] [spark] SongYadong commented on issue #23985: [SQL][MINOR] List SparkSql reserved keywords in alphabet order

2019-03-07 Thread GitBox
SongYadong commented on issue #23985: [SQL][MINOR] List SparkSql reserved 
keywords in alphabet order
URL: https://github.com/apache/spark/pull/23985#issuecomment-470838962
 
 
   @viirya thanks. I will do that.
   


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[GitHub] [spark] AmplabJenkins commented on issue #24023: [SPARK-27102][R][PYTHON][CORE] Remove the references to Python's Scala codes in R's Scala codes

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URL: https://github.com/apache/spark/pull/24023#issuecomment-470833089
 
 
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[GitHub] [spark] HyukjinKwon commented on issue #24023: [SPARK-27102][R][PYTHON][CORE] Remove the references to Python's Scala codes in R's Scala codes

2019-03-07 Thread GitBox
HyukjinKwon commented on issue #24023: [SPARK-27102][R][PYTHON][CORE] Remove 
the references to Python's Scala codes in R's Scala codes
URL: https://github.com/apache/spark/pull/24023#issuecomment-470832429
 
 
   cc @vanzin, @felixcheung, @squito 


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[GitHub] [spark] HyukjinKwon commented on a change in pull request #24023: [SPARK-27102][R][PYTHON][CORE] Remove the references to Python's Scala codes in R's Scala codes

2019-03-07 Thread GitBox
HyukjinKwon commented on a change in pull request #24023: 
[SPARK-27102][R][PYTHON][CORE] Remove the references to Python's Scala codes in 
R's Scala codes
URL: https://github.com/apache/spark/pull/24023#discussion_r263686438
 
 

 ##
 File path: core/src/main/scala/org/apache/spark/security/SocketAuthServer.scala
 ##
 @@ -0,0 +1,108 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.security
+
+import java.net._
+
+import scala.concurrent.Promise
+import scala.concurrent.duration.Duration
+import scala.language.existentials
+import scala.util.Try
+
+import org.apache.spark.SparkEnv
+import org.apache.spark.network.util.JavaUtils
+import org.apache.spark.util._
+
+
+/**
+ * Creates a server in the jvm to communicate with python for handling one 
batch of data, with
+ * authentication and error handling.
+ */
+private[spark] abstract class SocketAuthServer[T](
+authHelper: SocketAuthHelper,
+threadName: String) {
+
+  def this(env: SparkEnv, threadName: String) = this(new 
SocketAuthHelper(env.conf), threadName)
+  def this(threadName: String) = this(SparkEnv.get, threadName)
+
+  private val promise = Promise[T]()
 
 Review comment:
   All moved codes are as are, except that I made this `private`.


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[GitHub] [spark] HyukjinKwon opened a new pull request #24023: [SPARK-27102][R][PYTHON][CORE] Remove the references to Python's Scala codes in R's Scala codes

2019-03-07 Thread GitBox
HyukjinKwon opened a new pull request #24023: [SPARK-27102][R][PYTHON][CORE] 
Remove the references to Python's Scala codes in R's Scala codes
URL: https://github.com/apache/spark/pull/24023
 
 
   ## What changes were proposed in this pull request?
   
   Currently, R's Scala codes happened to refer Python's Scala codes for code 
deduplications. It's a bit odd. For instance, when we face an exception from R, 
it shows python related code path, which makes confusing to debug. It should 
rather have one code base and R's and Python's should share.
   
   This PR proposes:
   
   1. Make a `SocketAuthServer` and move `PythonServer` so that `PythonRDD` and 
`RRDD` can share it.
   2. Move `readRDDFromFile` and `readRDDFromInputStream` into `JavaRDD`.
   3. Reuse `RAuthHelper` and remove `RSocketAuthHelper` in `RRDD`.
   4. Rename `getEncryptionEnabled` to `isEncryptionEnabled` while I am here.
   
   So, now, the places below:
   
   - `sql/core/src/main/scala/org/apache/spark/sql/api/r`
   - `core/src/main/scala/org/apache/spark/api/r`
   - `mllib/src/main/scala/org/apache/spark/ml/r`
   
   don't refer Python's Scala codes.
   
   ## How was this patch tested?
   
   Existing tests should cover this.


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[GitHub] [spark] SparkQA commented on issue #23990: [SPARK-27061][K8S] Expose Driver UI port on driver service to access …

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[GitHub] [spark] SparkQA commented on issue #23942: [SPARK-27033][SQL]Add Optimize rule RewriteArithmeticFiltersOnIntegralColumn

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URL: https://github.com/apache/spark/pull/23942#issuecomment-470830534
 
 
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[GitHub] [spark] SparkQA commented on issue #23990: [SPARK-27061][K8S] Expose Driver UI port on driver service to access …

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URL: https://github.com/apache/spark/pull/23990#issuecomment-470830218
 
 
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[GitHub] [spark] hehuiyuan opened a new pull request #24022: [k8s] Add memory limit for kubernetes

2019-03-07 Thread GitBox
hehuiyuan opened a new pull request #24022: [k8s] Add memory limit  for 
kubernetes
URL: https://github.com/apache/spark/pull/24022
 
 
   ## What changes were proposed in this pull request?
   
   Add the limit memory to pod, distinguish limit memory from request memory.
   


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[GitHub] [spark] SparkQA commented on issue #23990: [SPARK-27061][K8S] Expose Driver UI port on driver service to access …

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[GitHub] [spark] chandulal commented on a change in pull request #23990: [SPARK-27061][K8S] Expose Driver UI port on driver service to access …

2019-03-07 Thread GitBox
chandulal commented on a change in pull request #23990: [SPARK-27061][K8S] 
Expose Driver UI port on driver service to access …
URL: https://github.com/apache/spark/pull/23990#discussion_r263681599
 
 

 ##
 File path: 
resource-managers/kubernetes/core/src/main/scala/org/apache/spark/deploy/k8s/features/DriverServiceFeatureStep.scala
 ##
 @@ -54,6 +56,8 @@ private[spark] class DriverServiceFeatureStep(
 config.DRIVER_PORT.key, DEFAULT_DRIVER_PORT)
   private val driverBlockManagerPort = kubernetesConf.sparkConf.getInt(
 config.DRIVER_BLOCK_MANAGER_PORT.key, DEFAULT_BLOCKMANAGER_PORT)
+  private val  driverUIPort = kubernetesConf.sparkConf.getInt(
 
 Review comment:
   Fixed this. 


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[GitHub] [spark] LantaoJin commented on a change in pull request #23951: [SPARK-27038][CORE][YARN] Re-implement RackResolver to reduce resolving time

2019-03-07 Thread GitBox
LantaoJin commented on a change in pull request #23951: 
[SPARK-27038][CORE][YARN] Re-implement RackResolver to reduce resolving time
URL: https://github.com/apache/spark/pull/23951#discussion_r263655647
 
 

 ##
 File path: 
core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala
 ##
 @@ -69,18 +69,48 @@ class FakeDAGScheduler(sc: SparkContext, taskScheduler: 
FakeTaskScheduler)
 // Get the rack for a given host
 object FakeRackUtil {
   private val hostToRack = new mutable.HashMap[String, String]()
+  var loopCount = 0
 
   def cleanUp() {
 hostToRack.clear()
+loopCount = 0
   }
 
   def assignHostToRack(host: String, rack: String) {
 hostToRack(host) = rack
   }
 
   def getRackForHost(host: String): Option[String] = {
+loopCount = simulateRunResolveCommand(Seq(host))
 hostToRack.get(host)
   }
+
+  def getRacksForHosts(hosts: List[String]): List[Option[String]] = {
+loopCount = simulateRunResolveCommand(hosts)
+hosts.map(hostToRack.get)
+  }
+
+  /**
+   * This is a simulation of building and executing the resolution command.
+   * Simulate function `runResolveCommand()` in 
[[org.apache.hadoop.net.ScriptBasedMapping]].
+   * If Seq has 100 elements, it returns 4. If Seq has 1 elements, it returns 
1.
+   * @param args a list of arguments
+   * @return script execution times
+   */
+  private def simulateRunResolveCommand(args: Seq[String]): Int = {
+val maxArgs = 30 // Simulate NET_TOPOLOGY_SCRIPT_NUMBER_ARGS_DEFAULT
+var numProcessed = 0
+var loopCount = 0
+while (numProcessed != args.size) {
+  var start = maxArgs * loopCount
+  numProcessed = start
+  while (numProcessed < (start + maxArgs) && numProcessed < args.size) {
+numProcessed += 1
+  }
+  loopCount += 1
+}
+loopCount
 
 Review comment:
   Why I added this complexity code for UT is that after applied this patch, 
the initializing processing of `TaskSetManager` won't invoke `getRackForHost()` 
any more. It has no place to count invocations for getRackForHost() vs counts 
of getRacksForHosts(). So I added this simulator to count the execution count 
of script. If this patch reversed, this `assert(FakeRackUtil.loopCount === 4)` 
will fail.
   For (3), I will add this kind of testing.


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[GitHub] [spark] SparkQA commented on issue #23964: [SPARK-26975][SQL] Support nested-column pruning over limit/sample/repartition

2019-03-07 Thread GitBox
SparkQA commented on issue #23964: [SPARK-26975][SQL] Support nested-column 
pruning over limit/sample/repartition
URL: https://github.com/apache/spark/pull/23964#issuecomment-470824584
 
 
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[GitHub] [spark] SparkQA commented on issue #23783: [SPARK-26854][SQL] Support ANY/SOME subquery

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URL: https://github.com/apache/spark/pull/23783#issuecomment-470824585
 
 
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[GitHub] [spark] dilipbiswal commented on issue #23783: [SPARK-26854][SQL] Support ANY/SOME subquery

2019-03-07 Thread GitBox
dilipbiswal commented on issue #23783: [SPARK-26854][SQL] Support ANY/SOME 
subquery
URL: https://github.com/apache/spark/pull/23783#issuecomment-470824260
 
 
   retest this please


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[GitHub] [spark] AmplabJenkins commented on issue #23964: [SPARK-26975][SQL] Support nested-column pruning over limit/sample/repartition

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[GitHub] [spark] hehuiyuan commented on a change in pull request #24009: [k8s]Unify the three variables' name : pod name prefix in kubernetes / spark.app.name in spark ui / spark-app-name in pod's ann

2019-03-07 Thread GitBox
hehuiyuan commented on a change in pull request #24009: [k8s]Unify the three 
variables' name :   pod name prefix in kubernetes / spark.app.name in spark 
ui  /  spark-app-name in pod's annotations
URL: https://github.com/apache/spark/pull/24009#discussion_r263679533
 
 

 ##
 File path: core/src/main/scala/org/apache/spark/SparkConf.scala
 ##
 @@ -115,9 +115,13 @@ class SparkConf(loadDefaults: Boolean) extends Cloneable 
with Logging with Seria
 set("spark.master", master)
   }
 
-  /** Set a name for your application. Shown in the Spark web UI. */
+  /** Set a name for your application. Shown in the Spark web UI.
+* For spark on kubernetes,Unify the three variables' name :
 
 Review comment:
   Thank you for your reply.


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[GitHub] [spark] maropu commented on issue #23964: [SPARK-26975][SQL] Support nested-column pruning over limit/sample/repartition

2019-03-07 Thread GitBox
maropu commented on issue #23964: [SPARK-26975][SQL] Support nested-column 
pruning over limit/sample/repartition
URL: https://github.com/apache/spark/pull/23964#issuecomment-470823410
 
 
   retest this please


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[GitHub] [spark] AmplabJenkins removed a comment on issue #24021: [SPARK-27101][Pyspark]Cleaning up the python testcases

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[GitHub] [spark] AmplabJenkins commented on issue #24021: [SPARK-27101][Pyspark]Cleaning up the python testcases

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[GitHub] [spark] sandeep-katta commented on issue #24021: [SPARK-27101][Pyspark]Cleaning up the python testcases

2019-03-07 Thread GitBox
sandeep-katta commented on issue #24021: [SPARK-27101][Pyspark]Cleaning up the 
python testcases
URL: https://github.com/apache/spark/pull/24021#issuecomment-470819616
 
 
   cc @HyukjinKwon @ueshin 


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[GitHub] [spark] sandeep-katta opened a new pull request #24021: [SPARK-27101][Pyspark]Cleaning up the python testcases

2019-03-07 Thread GitBox
sandeep-katta opened a new pull request #24021: [SPARK-27101][Pyspark]Cleaning 
up the python testcases
URL: https://github.com/apache/spark/pull/24021
 
 
   ## What changes were proposed in this pull request?
   
   Cleaning the testcase, drop the database after use
   
   ## How was this patch tested?
   
   existing UT
   


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[GitHub] [spark] SparkQA commented on issue #23982: [SPARK-27096][SQL] Reconcile the join types between data frame and sql interface

2019-03-07 Thread GitBox
SparkQA commented on issue #23982: [SPARK-27096][SQL] Reconcile the join types 
between data frame and sql interface
URL: https://github.com/apache/spark/pull/23982#issuecomment-470817813
 
 
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* This patch **fails SparkR unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.


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[GitHub] [spark] dilipbiswal commented on issue #24020: [MINOR][SQL]Fix the typo in the spark.sql.extensions conf doc

2019-03-07 Thread GitBox
dilipbiswal commented on issue #24020: [MINOR][SQL]Fix the typo in the 
spark.sql.extensions conf doc
URL: https://github.com/apache/spark/pull/24020#issuecomment-470817258
 
 
   Looks good to me. cc @maropu 


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[GitHub] [spark] SparkQA commented on issue #23982: [SPARK-27096][SQL] Reconcile the join types between data frame and sql interface

2019-03-07 Thread GitBox
SparkQA commented on issue #23982: [SPARK-27096][SQL] Reconcile the join types 
between data frame and sql interface
URL: https://github.com/apache/spark/pull/23982#issuecomment-470816756
 
 
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[GitHub] [spark] hddong commented on issue #23952: [SPARK-26929][SQL]fix table owner use user instead of principal when create table through spark-sql or beeline

2019-03-07 Thread GitBox
hddong commented on issue #23952: [SPARK-26929][SQL]fix table owner use user 
instead of principal when create table through spark-sql or beeline
URL: https://github.com/apache/spark/pull/23952#issuecomment-470815927
 
 
   @HyukjinKwon @felixcheung @vanzin , could you help to review this?


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[GitHub] [spark] AmplabJenkins commented on issue #24020: [MINOR][SQL]Fix the typo in the spark.sql.extensions conf doc

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URL: https://github.com/apache/spark/pull/24020#issuecomment-470814012
 
 
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[GitHub] [spark] SparkQA removed a comment on issue #23982: [SPARK-27096][SQL] Reconcile the join types between data frame and sql interface

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URL: https://github.com/apache/spark/pull/23982#issuecomment-470772941
 
 
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[GitHub] [spark] SparkQA commented on issue #23982: [SPARK-27096][SQL] Reconcile the join types between data frame and sql interface

2019-03-07 Thread GitBox
SparkQA commented on issue #23982: [SPARK-27096][SQL] Reconcile the join types 
between data frame and sql interface
URL: https://github.com/apache/spark/pull/23982#issuecomment-470813956
 
 
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* This patch **fails SparkR unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.


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[GitHub] [spark] skambha opened a new pull request #24020: [MINOR][SQL]Fix the typo in the SparkSessionExtensions class name

2019-03-07 Thread GitBox
skambha opened a new pull request #24020: [MINOR][SQL]Fix the typo in the 
SparkSessionExtensions class name
URL: https://github.com/apache/spark/pull/24020
 
 
   ## What changes were proposed in this pull request?
   Fix the  typo (missing the s)  in the class name (SparkSessionExtensions)  
in the doc for Spark conf spark.sql.extensions. 
   
   ## How was this patch tested?
   Verified by checking that the configuration doc shows up correctly in 
spark-shell using the SET -v 


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[GitHub] [spark] LantaoJin commented on a change in pull request #23951: [SPARK-27038][CORE][YARN] Re-implement RackResolver to reduce resolving time

2019-03-07 Thread GitBox
LantaoJin commented on a change in pull request #23951: 
[SPARK-27038][CORE][YARN] Re-implement RackResolver to reduce resolving time
URL: https://github.com/apache/spark/pull/23951#discussion_r263671020
 
 

 ##
 File path: 
core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala
 ##
 @@ -1602,4 +1637,27 @@ class TaskSetManagerSuite extends SparkFunSuite with 
LocalSparkContext with Logg
 verify(sched.dagScheduler).taskEnded(manager.tasks(3), Success, 
result.value(),
   result.accumUpdates, info3)
   }
+
+  test("SPARK-27038: Verify the rack resolving time has been reduced") {
+sc = new SparkContext("local", "test")
+for (i <- 1 to 100) {
+  FakeRackUtil.assignHostToRack("host" + i, "rack" + i)
+}
+sched = new FakeTaskScheduler(sc,
+  ("execA", "host1"), ("execB", "host2"), ("execC", "host3"))
+sched.slowRackResolve = true
+val locations = new ArrayBuffer[Seq[TaskLocation]]()
+for (i <- 1 to 100) {
+  locations += Seq(TaskLocation("host" + i))
+}
+val taskSet = FakeTask.createTaskSet(100, locations: _*)
+val clock = new ManualClock
+val manager = new TaskSetManager(sched, taskSet, MAX_TASK_FAILURES, clock 
= clock)
+var total = 0
+for (i <- 1 to 100) {
+  total += manager.getPendingTasksForRack("rack" + i).length
 
 Review comment:
   Yes. I will add.


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[GitHub] [spark] LantaoJin commented on a change in pull request #23951: [SPARK-27038][CORE][YARN] Re-implement RackResolver to reduce resolving time

2019-03-07 Thread GitBox
LantaoJin commented on a change in pull request #23951: 
[SPARK-27038][CORE][YARN] Re-implement RackResolver to reduce resolving time
URL: https://github.com/apache/spark/pull/23951#discussion_r263670931
 
 

 ##
 File path: core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala
 ##
 @@ -184,11 +184,23 @@ private[spark] class TaskSetManager(
 t.epoch = epoch
   }
 
+  // An array to store preferred location and its task index
+  private val locationWithTaskIndex: ArrayBuffer[(String, Int)] = new 
ArrayBuffer[(String, Int)]()
+  private val addTaskStartTime = System.nanoTime()
   // Add all our tasks to the pending lists. We do this in reverse order
   // of task index so that tasks with low indices get launched first.
   for (i <- (0 until numTasks).reverse) {
-addPendingTask(i)
+addPendingTask(i, true)
   }
+  // Convert preferred location list to rack list in one invocation and zip 
with the origin index
+  private val rackWithTaskIndex = 
sched.getRacksForHosts(locationWithTaskIndex.map(_._1).toList)
 
 Review comment:
   > The de-duping thing is minor, but I am concerned that the 
`locationWithTaskIndex` variable is going to be confusing if its left around as 
a private member variable, even though its only meaningful in this limited 
context.
   
   Yes, I don't want to do any de-duping here. I will refactor this part for 
getting more readable.
   


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[GitHub] [spark] LantaoJin commented on a change in pull request #23951: [SPARK-27038][CORE][YARN] Re-implement RackResolver to reduce resolving time

2019-03-07 Thread GitBox
LantaoJin commented on a change in pull request #23951: 
[SPARK-27038][CORE][YARN] Re-implement RackResolver to reduce resolving time
URL: https://github.com/apache/spark/pull/23951#discussion_r263670454
 
 

 ##
 File path: 
core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala
 ##
 @@ -69,18 +69,48 @@ class FakeDAGScheduler(sc: SparkContext, taskScheduler: 
FakeTaskScheduler)
 // Get the rack for a given host
 object FakeRackUtil {
   private val hostToRack = new mutable.HashMap[String, String]()
+  var loopCount = 0
 
   def cleanUp() {
 hostToRack.clear()
+loopCount = 0
   }
 
   def assignHostToRack(host: String, rack: String) {
 hostToRack(host) = rack
   }
 
   def getRackForHost(host: String): Option[String] = {
+loopCount = simulateRunResolveCommand(Seq(host))
 hostToRack.get(host)
   }
+
+  def getRacksForHosts(hosts: List[String]): List[Option[String]] = {
+loopCount = simulateRunResolveCommand(hosts)
+hosts.map(hostToRack.get)
+  }
+
+  /**
+   * This is a simulation of building and executing the resolution command.
+   * Simulate function `runResolveCommand()` in 
[[org.apache.hadoop.net.ScriptBasedMapping]].
+   * If Seq has 100 elements, it returns 4. If Seq has 1 elements, it returns 
1.
+   * @param args a list of arguments
+   * @return script execution times
+   */
+  private def simulateRunResolveCommand(args: Seq[String]): Int = {
+val maxArgs = 30 // Simulate NET_TOPOLOGY_SCRIPT_NUMBER_ARGS_DEFAULT
+var numProcessed = 0
+var loopCount = 0
+while (numProcessed != args.size) {
+  var start = maxArgs * loopCount
+  numProcessed = start
+  while (numProcessed < (start + maxArgs) && numProcessed < args.size) {
+numProcessed += 1
+  }
+  loopCount += 1
+}
+loopCount
 
 Review comment:
   > Would it be worth also adding a test for (2) somehow? I'm not sure what 
you could do there without it being tied to the internals of the hadoop logic. 
You could test the instance of the created
   
   This part has tested in Hadoop and I just create an instance of 
`CachedDNSToSwitchMapping`:
   ```
  dnsToSwitchMapping = newInstance match {
 case _: CachedDNSToSwitchMapping => newInstance
 case _ => new CachedDNSToSwitchMapping(newInstance)
   }
   ```
   So I think it doesn't need to add a test for the cache.
   


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