update for Spark 1.5.1

all-spark-notebook/Dockerfile

@@ -6,7 +6,7 @@ MAINTAINER Jupyter Project <jupyter@googlegroups.com>
 USER root
 
 # Spark dependencies
-ENV APACHE_SPARK_VERSION 1.4.1
+ENV APACHE_SPARK_VERSION 1.5.1
 RUN apt-get -y update && \
     apt-get install -y --no-install-recommends openjdk-7-jre-headless && \
     apt-get clean

all-spark-notebook/README.md

@@ -8,7 +8,7 @@
 * Scala 2.10.x
 * pyspark, pandas, matplotlib, scipy, seaborn, scikit-learn pre-installed for Python
 * ggplot2, rcurl preinstalled for R
-* Spark 1.4.1 for use in local mode or to connect to a cluster of Spark workers
+* Spark 1.5.1 for use in local mode or to connect to a cluster of Spark workers
 * Mesos client 0.22 binary that can communicate with a Mesos master
 * Unprivileged user `jovyan` (uid=1000, configurable, see options) in group `users` (gid=100) with ownership over `/home/jovyan` and `/opt/conda`
 * [tini](https://github.com/krallin/tini) as the container entrypoint and [start-notebook.sh](../minimal-notebook/start-notebook.sh) as the default command
@@ -114,8 +114,8 @@ conf = pyspark.SparkConf()
 # point to mesos master or zookeeper entry (e.g., zk://10.10.10.10:2181/mesos)
 conf.setMaster("mesos://10.10.10.10:5050")
 # point to spark binary package in HDFS or on local filesystem on all slave
-# nodes (e.g., file:///opt/spark/spark-1.4.1-bin-hadoop2.6.tgz) 
-conf.set("spark.executor.uri", "hdfs://10.10.10.10/spark/spark-1.4.1-bin-hadoop2.6.tgz")
+# nodes (e.g., file:///opt/spark/spark-1.5.1-bin-hadoop2.6.tgz) 
+conf.set("spark.executor.uri", "hdfs://10.10.10.10/spark/spark-1.5.1-bin-hadoop2.6.tgz")
 # set other options as desired
 conf.set("spark.executor.memory", "8g")
 conf.set("spark.core.connection.ack.wait.timeout", "1200")
@@ -147,10 +147,10 @@ library(SparkR)
 # point to mesos master or zookeeper entry (e.g., zk://10.10.10.10:2181/mesos)\
 # as the first argument
 # point to spark binary package in HDFS or on local filesystem on all slave
-# nodes (e.g., file:///opt/spark/spark-1.4.1-bin-hadoop2.6.tgz) in sparkEnvir
+# nodes (e.g., file:///opt/spark/spark-1.5.1-bin-hadoop2.6.tgz) in sparkEnvir
 # set other options in sparkEnvir
 sc <- sparkR.init("mesos://10.10.10.10:5050", sparkEnvir=list(
-    spark.executor.uri="hdfs://10.10.10.10/spark/spark-1.4.1-bin-hadoop2.6.tgz",
+    spark.executor.uri="hdfs://10.10.10.10/spark/spark-1.5.1-bin-hadoop2.6.tgz",
     spark.executor.memory="8g"
     )
 )
@@ -184,7 +184,7 @@ For instance, a kernel spec file with information about a Mesos master, Spark bi
         "--master=mesos://10.10.10.10:5050"
     ],
     "env": {
-        "SPARK_CONFIGURATION": "spark.executor.memory=8g,spark.executor.uri=hdfs://10.10.10.10/spark/spark-1.4.1-bin-hadoop2.6.tgz"
+        "SPARK_CONFIGURATION": "spark.executor.memory=8g,spark.executor.uri=hdfs://10.10.10.10/spark/spark-1.5.1-bin-hadoop2.6.tgz"
     }
 }
 ```

pyspark-notebook/Dockerfile

@@ -6,7 +6,7 @@ MAINTAINER Jupyter Project <jupyter@googlegroups.com>
 USER root
 
 # Spark dependencies
-ENV APACHE_SPARK_VERSION 1.4.1
+ENV APACHE_SPARK_VERSION 1.5.1
 RUN apt-get -y update && \
     apt-get install -y --no-install-recommends openjdk-7-jre-headless && \
     apt-get clean

pyspark-notebook/README.md

@@ -5,7 +5,7 @@
 * Jupyter Notebook 4.0.x
 * Conda Python 3.x and Python 2.7.x environments
 * pyspark, pandas, matplotlib, scipy, seaborn, scikit-learn pre-installed
-* Spark 1.4.1 for use in local mode or to connect to a cluster of Spark workers
+* Spark 1.5.1 for use in local mode or to connect to a cluster of Spark workers
 * Mesos client 0.22 binary that can communicate with a Mesos master
 * Unprivileged user `jovyan` (uid=1000, configurable, see options) in group `users` (gid=100) with ownership over `/home/jovyan` and `/opt/conda`
 * [tini](https://github.com/krallin/tini) as the container entrypoint and [start-notebook.sh](../minimal-notebook/start-notebook.sh) as the default command
@@ -72,8 +72,8 @@ conf = pyspark.SparkConf()
 # point to mesos master or zookeeper entry (e.g., zk://10.10.10.10:2181/mesos)
 conf.setMaster("mesos://10.10.10.10:5050")
 # point to spark binary package in HDFS or on local filesystem on all slave
-# nodes (e.g., file:///opt/spark/spark-1.4.1-bin-hadoop2.6.tgz) 
-conf.set("spark.executor.uri", "hdfs://10.122.193.209/spark/spark-1.4.1-bin-hadoop2.6.tgz")
+# nodes (e.g., file:///opt/spark/spark-1.5.1-bin-hadoop2.6.tgz) 
+conf.set("spark.executor.uri", "hdfs://10.122.193.209/spark/spark-1.5.1-bin-hadoop2.6.tgz")
 # set other options as desired
 conf.set("spark.executor.memory", "8g")
 conf.set("spark.core.connection.ack.wait.timeout", "1200")