Merge pull request #462 from mateiz/conf-file-fix

Remove Typesafe Config usage and conf files to fix nested property names

With Typesafe Config we had the subtle problem of no longer allowing
nested property names, which are used for a few of our properties:
http://apache-spark-developers-list.1001551.n3.nabble.com/Config-properties-broken-in-master-td208.html

This PR is for branch 0.9 but should be added into master too.

core/src/main/scala/org/apache/spark/SparkConf.scala

@@ -20,19 +20,17 @@ package org.apache.spark
 import scala.collection.JavaConverters._
 import scala.collection.mutable.HashMap
 
-import com.typesafe.config.ConfigFactory
 import java.io.{ObjectInputStream, ObjectOutputStream, IOException}
 
 /**
  * Configuration for a Spark application. Used to set various Spark parameters as key-value pairs.
  *
  * Most of the time, you would create a SparkConf object with `new SparkConf()`, which will load
- * values from both the `spark.*` Java system properties and any `spark.conf` on your application's
+ * values from any `spark.*` Java system properties set in your application as well. In this case,
- * classpath (if it has one). In this case, system properties take priority over `spark.conf`, and
+ * parameters you set directly on the `SparkConf` object take priority over system properties.
- * any parameters you set directly on the `SparkConf` object take priority over both of those.
  *
  * For unit tests, you can also call `new SparkConf(false)` to skip loading external settings and
- * get the same configuration no matter what is on the classpath.
+ * get the same configuration no matter what the system properties are.
  *
  * All setter methods in this class support chaining. For example, you can write
  * `new SparkConf().setMaster("local").setAppName("My app")`.
@@ -40,7 +38,7 @@ import java.io.{ObjectInputStream, ObjectOutputStream, IOException}
  * Note that once a SparkConf object is passed to Spark, it is cloned and can no longer be modified
  * by the user. Spark does not support modifying the configuration at runtime.
  *
- * @param loadDefaults whether to load values from the system properties and classpath
+ * @param loadDefaults whether to also load values from Java system properties
  */
 class SparkConf(loadDefaults: Boolean) extends Cloneable with Logging {
 
@@ -50,11 +48,9 @@ class SparkConf(loadDefaults: Boolean) extends Cloneable with Logging {
   private val settings = new HashMap[String, String]()
 
   if (loadDefaults) {
-    ConfigFactory.invalidateCaches()
+    // Load any spark.* system properties
-    val typesafeConfig = ConfigFactory.systemProperties()
+    for ((k, v) <- System.getProperties.asScala if k.startsWith("spark.")) {
-      .withFallback(ConfigFactory.parseResources("spark.conf"))
+      settings(k) = v
-    for (e <- typesafeConfig.entrySet().asScala if e.getKey.startsWith("spark.")) {
-      settings(e.getKey) = e.getValue.unwrapped.toString
     }
   }
 

core/src/test/resources/spark.conf

@@ -1,8 +0,0 @@
-# A simple spark.conf file used only in our unit tests
-
-spark.test.intTestProperty = 1
-
-spark.test {
-  stringTestProperty = "hi"
-  listTestProperty = ["a", "b"]
-}

core/src/test/scala/org/apache/spark/SparkConfSuite.scala

@@ -20,35 +20,23 @@ package org.apache.spark
 import org.scalatest.FunSuite
 
 class SparkConfSuite extends FunSuite with LocalSparkContext {
-  // This test uses the spark.conf in core/src/test/resources, which has a few test properties
+  test("loading from system properties") {
-  test("loading from spark.conf") {
-    val conf = new SparkConf()
-    assert(conf.get("spark.test.intTestProperty") === "1")
-    assert(conf.get("spark.test.stringTestProperty") === "hi")
-    // NOTE: we don't use list properties yet, but when we do, we'll have to deal with this syntax
-    assert(conf.get("spark.test.listTestProperty") === "[a, b]")
-  }
-
-  // This test uses the spark.conf in core/src/test/resources, which has a few test properties
-  test("system properties override spark.conf") {
     try {
-      System.setProperty("spark.test.intTestProperty", "2")
+      System.setProperty("spark.test.testProperty", "2")
       val conf = new SparkConf()
-      assert(conf.get("spark.test.intTestProperty") === "2")
+      assert(conf.get("spark.test.testProperty") === "2")
-      assert(conf.get("spark.test.stringTestProperty") === "hi")
     } finally {
-      System.clearProperty("spark.test.intTestProperty")
+      System.clearProperty("spark.test.testProperty")
     }
   }
 
   test("initializing without loading defaults") {
     try {
-      System.setProperty("spark.test.intTestProperty", "2")
+      System.setProperty("spark.test.testProperty", "2")
       val conf = new SparkConf(false)
-      assert(!conf.contains("spark.test.intTestProperty"))
+      assert(!conf.contains("spark.test.testProperty"))
-      assert(!conf.contains("spark.test.stringTestProperty"))
     } finally {
-      System.clearProperty("spark.test.intTestProperty")
+      System.clearProperty("spark.test.testProperty")
     }
   }
 
@@ -124,4 +112,25 @@ class SparkConfSuite extends FunSuite with LocalSparkContext {
     assert(sc.master === "local[2]")
     assert(sc.appName === "My other app")
   }
+
+  test("nested property names") {
+    // This wasn't supported by some external conf parsing libraries
+    try {
+      System.setProperty("spark.test.a", "a")
+      System.setProperty("spark.test.a.b", "a.b")
+      System.setProperty("spark.test.a.b.c", "a.b.c")
+      val conf = new SparkConf()
+      assert(conf.get("spark.test.a") === "a")
+      assert(conf.get("spark.test.a.b") === "a.b")
+      assert(conf.get("spark.test.a.b.c") === "a.b.c")
+      conf.set("spark.test.a.b", "A.B")
+      assert(conf.get("spark.test.a") === "a")
+      assert(conf.get("spark.test.a.b") === "A.B")
+      assert(conf.get("spark.test.a.b.c") === "a.b.c")
+    } finally {
+      System.clearProperty("spark.test.a")
+      System.clearProperty("spark.test.a.b")
+      System.clearProperty("spark.test.a.b.c")
+    }
+  }
 }

docs/configuration.md

@@ -18,8 +18,8 @@ Spark provides three locations to configure the system:
 Spark properties control most application settings and are configured separately for each application.
 The preferred way to set them is by passing a [SparkConf](api/core/index.html#org.apache.spark.SparkConf)
 class to your SparkContext constructor.
-Alternatively, Spark will also load them from Java system properties (for compatibility with old versions
+Alternatively, Spark will also load them from Java system properties, for compatibility with old versions
-of Spark) and from a [`spark.conf` file](#configuration-files) on your classpath.
+of Spark.
 
 SparkConf lets you configure most of the common properties to initialize a cluster (e.g., master URL and
 application name), as well as arbitrary key-value pairs through the `set()` method. For example, we could
@@ -468,30 +468,6 @@ Apart from these, the following properties are also available, and may be useful
 The application web UI at `http://<driver>:4040` lists Spark properties in the "Environment" tab.
 This is a useful place to check to make sure that your properties have been set correctly.
 
-## Configuration Files
-
-You can also configure Spark properties through a `spark.conf` file on your Java classpath.
-Because these properties are usually application-specific, we recommend putting this fine *only* on your
-application's classpath, and not in a global Spark classpath.
-
-The `spark.conf` file uses Typesafe Config's [HOCON format](https://github.com/typesafehub/config#json-superset),
-which is a superset of Java properties files and JSON. For example, the following is a simple config file:
-
-{% highlight awk %}
-# Comments are allowed
-spark.executor.memory = 512m
-spark.serializer = org.apache.spark.serializer.KryoSerializer
-{% endhighlight %}
-
-The format also allows hierarchical nesting, as follows:
-
-{% highlight awk %}
-spark.akka {
-  threads = 8
-  timeout = 200
-}
-{% endhighlight %}
-
 # Environment Variables
 
 Certain Spark settings can be configured through environment variables, which are read from the `conf/spark-env.sh`

project/SparkBuild.scala

@@ -277,7 +277,6 @@ object SparkBuild extends Build {
         "com.codahale.metrics"     % "metrics-graphite" % "3.0.0",
         "com.twitter"             %% "chill"            % "0.3.1",
         "com.twitter"              % "chill-java"       % "0.3.1",
-        "com.typesafe"             % "config"           % "1.0.2",
         "com.clearspring.analytics" % "stream"          % "2.5.1"
       )
   )

python/pyspark/conf.py

@@ -61,14 +61,12 @@ class SparkConf(object):
 
     Most of the time, you would create a SparkConf object with
     C{SparkConf()}, which will load values from C{spark.*} Java system
-    properties and any C{spark.conf} on your Spark classpath. In this
+    properties as well. In this case, any parameters you set directly on
-    case, system properties take priority over C{spark.conf}, and any
+    the C{SparkConf} object take priority over system properties.
-    parameters you set directly on the C{SparkConf} object take priority
-    over both of those.
 
     For unit tests, you can also call C{SparkConf(false)} to skip
     loading external settings and get the same configuration no matter
-    what is on the classpath.
+    what the system properties are.
 
     All setter methods in this class support chaining. For example,
     you can write C{conf.setMaster("local").setAppName("My app")}.
@@ -82,7 +80,7 @@ class SparkConf(object):
         Create a new Spark configuration.
 
         @param loadDefaults: whether to load values from Java system
-               properties and classpath (True by default)
+               properties (True by default)
         @param _jvm: internal parameter used to pass a handle to the
                Java VM; does not need to be set by users
         """