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Posted to commits@systemml.apache.org by de...@apache.org on 2017/04/07 18:58:35 UTC
[31/50] [abbrv] incubator-systemml git commit: Updated document to
correspond to the currently released artifacts
Updated document to correspond to the currently released artifacts
Closes #403
Project: http://git-wip-us.apache.org/repos/asf/incubator-systemml/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-systemml/commit/5c4e27c7
Tree: http://git-wip-us.apache.org/repos/asf/incubator-systemml/tree/5c4e27c7
Diff: http://git-wip-us.apache.org/repos/asf/incubator-systemml/diff/5c4e27c7
Branch: refs/heads/gh-pages
Commit: 5c4e27c701da1084d1e47d7ad049f9570033e7ae
Parents: 0fb74b9
Author: Nakul Jindal <na...@gmail.com>
Authored: Tue Feb 21 14:56:58 2017 -0800
Committer: Nakul Jindal <na...@gmail.com>
Committed: Thu Feb 23 13:20:27 2017 -0800
----------------------------------------------------------------------
release-process.md | 146 ++++++++++++++++++++----------------------------
1 file changed, 62 insertions(+), 84 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/incubator-systemml/blob/5c4e27c7/release-process.md
----------------------------------------------------------------------
diff --git a/release-process.md b/release-process.md
index 1cc5c9f..a75a281 100644
--- a/release-process.md
+++ b/release-process.md
@@ -102,86 +102,64 @@ The build artifacts should be downloaded from [https://dist.apache.org/repos/dis
this OS X example.
# download artifacts
- wget -r -nH -nd -np -R index.html* https://dist.apache.org/repos/dist/dev/incubator/systemml/0.11.0-incubating-rc1/
+ wget -r -nH -nd -np -R 'index.html*' https://dist.apache.org/repos/dist/dev/incubator/systemml/0.13.0-incubating-rc1/
# verify standalone tgz works
- tar -xvzf systemml-0.11.0-incubating-standalone.tgz
- cd systemml-0.11.0-incubating-standalone
+ tar -xvzf systemml-0.13.0-incubating-bin.tgz
+ cd systemml-0.13.0-incubating-bin
echo "print('hello world');" > hello.dml
./runStandaloneSystemML.sh hello.dml
cd ..
- # verify main jar works
- mkdir lib
- cp -R systemml-0.11.0-incubating-standalone/lib/* lib/
- rm lib/systemml-0.11.0-incubating.jar
- java -cp ./lib/*:systemml-0.11.0-incubating.jar org.apache.sysml.api.DMLScript -s "print('hello world');"
-
- # verify src works
- tar -xvzf systemml-0.11.0-incubating-src.tgz
- cd systemml-0.11.0-incubating-src
- mvn clean package -P distribution
- cd target/
- java -cp ./lib/*:systemml-0.11.0-incubating.jar org.apache.sysml.api.DMLScript -s "print('hello world');"
- java -cp ./lib/*:SystemML.jar org.apache.sysml.api.DMLScript -s "print('hello world');"
- cd ..
+ # verify standalon zip works
+ rm -rf systemml-0.13.0-incubating-bin
+ unzip systemml-0.13.0-incubating-bin.zip
+ cd systemml-0.13.0-incubating-bin
+ echo "print('hello world');" > hello.dml
+ ./runStandaloneSystemML.sh hello.dml
cd ..
- # verify distrib tgz works
- tar -xvzf systemml-0.11.0-incubating.tgz
- cd systemml-0.11.0-incubating
- java -cp ../lib/*:SystemML.jar org.apache.sysml.api.DMLScript -s "print('hello world');"
-
- # verify spark batch mode
- export SPARK_HOME=/Users/deroneriksson/spark-1.5.1-bin-hadoop2.6
- $SPARK_HOME/bin/spark-submit SystemML.jar -s "print('hello world');" -exec hybrid_spark
-
- # verify hadoop batch mode
- hadoop jar SystemML.jar -s "print('hello world');"
-
-
-Here is an example of doing a basic
-sanity check on OS X after building the artifacts manually.
-
- # build distribution artifacts
- mvn clean package -P distribution
-
- cd target
-
- # verify main jar works
- java -cp ./lib/*:systemml-0.11.0-incubating.jar org.apache.sysml.api.DMLScript -s "print('hello world');"
-
- # verify SystemML.jar works
- java -cp ./lib/*:SystemML.jar org.apache.sysml.api.DMLScript -s "print('hello world');"
-
# verify src works
- tar -xvzf systemml-0.11.0-incubating-src.tgz
- cd systemml-0.11.0-incubating-src
+ tar -xvzf systemml-0.13.0-incubating-src.tgz
+ cd systemml-0.13.0-incubating-src
mvn clean package -P distribution
cd target/
- java -cp ./lib/*:systemml-0.11.0-incubating.jar org.apache.sysml.api.DMLScript -s "print('hello world');"
- java -cp ./lib/*:SystemML.jar org.apache.sysml.api.DMLScript -s "print('hello world');"
- cd ..
- cd ..
-
- # verify standalone tgz works
- tar -xvzf systemml-0.11.0-incubating-standalone.tgz
- cd systemml-0.11.0-incubating-standalone
- echo "print('hello world');" > hello.dml
- ./runStandaloneSystemML.sh hello.dml
- cd ..
-
- # verify distrib tgz works
- tar -xvzf systemml-0.11.0-incubating.tgz
- cd systemml-0.11.0-incubating
- java -cp ../lib/*:SystemML.jar org.apache.sysml.api.DMLScript -s "print('hello world');"
+ java -cp "./lib/*:systemml-0.13.0-incubating.jar" org.apache.sysml.api.DMLScript -s "print('hello world');"
+ java -cp "./lib/*:SystemML.jar" org.apache.sysml.api.DMLScript -s "print('hello world');"
+ cd ../..
# verify spark batch mode
- export SPARK_HOME=/Users/deroneriksson/spark-1.5.1-bin-hadoop2.6
- $SPARK_HOME/bin/spark-submit SystemML.jar -s "print('hello world');" -exec hybrid_spark
+ export SPARK_HOME=~/spark-2.1.0-bin-hadoop2.7
+ cd systemml-0.13.0-incubating-bin/target/lib
+ $SPARK_HOME/bin/spark-submit systemml-0.13.0-incubating.jar -s "print('hello world');" -exec hybrid_spark
# verify hadoop batch mode
- hadoop jar SystemML.jar -s "print('hello world');"
+ hadoop jar systemml-0.13.0-incubating.jar -s "print('hello world');"
+
+
+ # verify python artifact
+ # install numpy, pandas, scipy & set SPARK_HOME
+ pip install numpy
+ pip install pandas
+ pip install scipy
+ export SPARK_HOME=~/spark-2.1.0-bin-hadoop2.7
+ # get into the pyspark prompt
+ cd systemml-0.13.0
+ $SPARK_HOME/bin/pyspark --driver-class-path systemml-java/systemml-0.13.0-incubating.jar
+ # Use this program at the prompt:
+ import systemml as sml
+ import numpy as np
+ m1 = sml.matrix(np.ones((3,3)) + 2)
+ m2 = sml.matrix(np.ones((3,3)) + 3)
+ m2 = m1 * (m2 + m1)
+ m4 = 1.0 - m2
+ m4.sum(axis=1).toNumPy()
+
+ # This should be printed
+ # array([[-60.],
+ # [-60.],
+ # [-60.]])
+
## Python Tests
@@ -229,8 +207,8 @@ The project should be built using the `src` (tgz and zip) artifacts.
In addition, the test suite should be run using an `src` artifact and
the tests should pass.
- tar -xvzf systemml-0.11.0-incubating-src.tgz
- cd systemml-0.11.0-incubating-src
+ tar -xvzf systemml-0.13.0-incubating-src.tgz
+ cd systemml-0.13.0-incubating-src
mvn clean package -P distribution
mvn verify
@@ -246,13 +224,14 @@ standalone distributions.
Here is an example based on the [Standalone Guide](http://apache.github.io/incubator-systemml/standalone-guide.html)
demonstrating the execution of an algorithm (on OS X).
- $ tar -xvzf systemml-0.11.0-incubating-standalone.tgz
- $ cd systemml-0.11.0-incubating-standalone
- $ wget -P data/ http://archive.ics.uci.edu/ml/machine-learning-databases/haberman/haberman.data
- $ echo '{"rows": 306, "cols": 4, "format": "csv"}' > data/haberman.data.mtd
- $ echo '1,1,1,2' > data/types.csv
- $ echo '{"rows": 1, "cols": 4, "format": "csv"}' > data/types.csv.mtd
- $ ./runStandaloneSystemML.sh scripts/algorithms/Univar-Stats.dml -nvargs X=data/haberman.data TYPES=data/types.csv STATS=data/univarOut.mtx CONSOLE_OUTPUT=TRUE
+ tar -xvzf systemml-0.13.0-incubating-bin.tgz
+ cd systemml-0.13.0-incubating-bin
+ wget -P data/ http://archive.ics.uci.edu/ml/machine-learning-databases/haberman/haberman.data
+ echo '{"rows": 306, "cols": 4, "format": "csv"}' > data/haberman.data.mtd
+ echo '1,1,1,2' > data/types.csv
+ echo '{"rows": 1, "cols": 4, "format": "csv"}' > data/types.csv.mtd
+ ./runStandaloneSystemML.sh scripts/algorithms/Univar-Stats.dml -nvargs X=data/haberman.data TYPES=data/types.csv STATS=data/univarOut.mtx CONSOLE_OUTPUT=TRUE
+ cd ..
## Single-Node Spark
@@ -263,13 +242,13 @@ Verify that SystemML runs algorithms on Spark locally.
Here is an example of running the `Univar-Stats.dml` algorithm on random generated data.
- $ tar -xvzf systemml-0.11.0-incubating.tgz
- $ cd systemml-0.11.0-incubating
- $ export SPARK_HOME=/Users/deroneriksson/spark-1.5.1-bin-hadoop2.6
- $ $SPARK_HOME/bin/spark-submit SystemML.jar -f scripts/datagen/genRandData4Univariate.dml -exec hybrid_spark -args 1000000 100 10 1 2 3 4 uni.mtx
- $ echo '1' > uni-types.csv
- $ echo '{"rows": 1, "cols": 1, "format": "csv"}' > uni-types.csv.mtd
- $ $SPARK_HOME/bin/spark-submit SystemML.jar -f scripts/algorithms/Univar-Stats.dml -exec hybrid_spark -nvargs X=uni.mtx TYPES=uni-types.csv STATS=uni-stats.txt CONSOLE_OUTPUT=TRUE
+ cd systemml-0.13.0-incubating-bin/lib
+ export SPARK_HOME=~/spark-2.1.0-bin-hadoop2.7
+ $SPARK_HOME/bin/spark-submit systemml-0.13.0-incubating.jar -f ../scripts/datagen/genRandData4Univariate.dml -exec hybrid_spark -args 1000000 100 10 1 2 3 4 uni.mtx
+ echo '1' > uni-types.csv
+ echo '{"rows": 1, "cols": 1, "format": "csv"}' > uni-types.csv.mtd
+ $SPARK_HOME/bin/spark-submit systemml-0.13.0-incubating.jar -f ../scripts/algorithms/Univar-Stats.dml -exec hybrid_spark -nvargs X=uni.mtx TYPES=uni-types.csv STATS=uni-stats.txt CONSOLE_OUTPUT=TRUE
+ cd ..
## Single-Node Hadoop
@@ -280,7 +259,8 @@ Verify that SystemML runs algorithms on Hadoop locally.
Based on the "Single-Node Spark" setup above, the `Univar-Stats.dml` algorithm could be run as follows:
- $ hadoop jar SystemML.jar -f scripts/algorithms/Univar-Stats.dml -nvargs X=uni.mtx TYPES=uni-types.csv STATS=uni-stats.txt CONSOLE_OUTPUT=TRUE
+ cd systemml-0.13.0-incubating-bin/lib
+ hadoop jar systemml-0.13.0-incubating.jar -f ../scripts/algorithms/Univar-Stats.dml -nvargs X=uni.mtx TYPES=uni-types.csv STATS=uni-stats.txt CONSOLE_OUTPUT=TRUE
## Notebooks
@@ -313,5 +293,3 @@ has been approved.
To be written. (What steps need to be done? How is the release deployed to the central maven repo? What updates need to
happen to the main website, such as updating the Downloads page? Where do the release notes for the release go?)
-
-