1 files changed, 5 insertions, 5 deletions
diff --git a/docs/quick-start.md b/docs/quick-start.md
index a4c4c9a8fb..216f7c9cc5 100644
--- a/docs/quick-start.md
+++ b/docs/quick-start.md
@@ -136,7 +136,7 @@ scalaVersion := "{{site.SCALA_VERSION}}"
 libraryDependencies += "org.spark-project" %% "spark-core" % "{{site.SPARK_VERSION}}"
 
 resolvers ++= Seq(
-  "Typesafe Repository" at "http://repo.typesafe.com/typesafe/releases/",
+  "Akka Repository" at "http://repo.akka.io/releases/",
   "Spray Repository" at "http://repo.spray.cc/")
 {% endhighlight %}
 
@@ -189,7 +189,7 @@ public class SimpleJob {
 }
 {% endhighlight %}
 
-This job simply counts the number of lines containing 'a' and the number containing 'b' in a system log file. Note that like in the Scala example, we initialize a SparkContext, though we use the special `JavaSparkContext` class to get a Java-friendly one. We also create RDDs (represented by `JavaRDD`) and run transformations on them. Finally, we pass functions to Spark by creating classes that extend `spark.api.java.function.Function`. The [Java programming guide]("java-programming-guide") describes these differences in more detail.
+This job simply counts the number of lines containing 'a' and the number containing 'b' in a system log file. Note that like in the Scala example, we initialize a SparkContext, though we use the special `JavaSparkContext` class to get a Java-friendly one. We also create RDDs (represented by `JavaRDD`) and run transformations on them. Finally, we pass functions to Spark by creating classes that extend `spark.api.java.function.Function`. The [Java programming guide](java-programming-guide.html) describes these differences in more detail.
 
 To build the job, we also write a Maven `pom.xml` file that lists Spark as a dependency. Note that Spark artifacts are tagged with a Scala version.
 
@@ -207,8 +207,8 @@ To build the job, we also write a Maven `pom.xml` file that lists Spark as a dep
       <url>http://repo.spray.cc</url>
     </repository>
     <repository>
-      <id>Typesafe repository</id>
-      <url>http://repo.typesafe.com/typesafe/releases</url>
+      <id>Akka repository</id>
+      <url>http://repo.akka.io/releases</url>
     </repository>
   </repositories>
   <dependencies>
@@ -265,7 +265,7 @@ print "Lines with a: %i, lines with b: %i" % (numAs, numBs)
 This job simply counts the number of lines containing 'a' and the number containing 'b' in a system log file.
 Like in the Scala and Java examples, we use a SparkContext to create RDDs.
 We can pass Python functions to Spark, which are automatically serialized along with any variables that they reference.
-For jobs that use custom classes or third-party libraries, we can add those code dependencies to SparkContext to ensure that they will be available on remote machines; this is described in more detail in the [Python programming guide](python-programming-guide).
+For jobs that use custom classes or third-party libraries, we can add those code dependencies to SparkContext to ensure that they will be available on remote machines; this is described in more detail in the [Python programming guide](python-programming-guide.html).
 `SimpleJob` is simple enough that we do not need to specify any code dependencies.
 
 We can run this job using the `pyspark` script: