0e16a6f5b0
## What changes were proposed in this pull request? I happened to meet this case few times before: ``` Enter comma-separated fix version(s) [3.0.0]: 3.0,0 Restoring head pointer to master git checkout master Already on 'master' git branch Traceback (most recent call last): File "./dev/merge_spark_pr_jira.py", line 537, in <module> main() File "./dev/merge_spark_pr_jira.py", line 523, in main resolve_jira_issues(title, merged_refs, jira_comment) File "./dev/merge_spark_pr_jira.py", line 359, in resolve_jira_issues resolve_jira_issue(merge_branches, comment, jira_id) File "./dev/merge_spark_pr_jira.py", line 302, in resolve_jira_issue jira_fix_versions = map(lambda v: get_version_json(v), fix_versions) File "./dev/merge_spark_pr_jira.py", line 302, in <lambda> jira_fix_versions = map(lambda v: get_version_json(v), fix_versions) File "./dev/merge_spark_pr_jira.py", line 300, in get_version_json return filter(lambda v: v.name == version_str, versions)[0].raw IndexError: list index out of range ``` I typed the fix version wrongly (there's comma in `3.0,0`) and it ended the loop in the merge script. Not a big deal but it bugged me few times. Finally I met this today again, and decided to fix. This PR proposes to recover from wrongly set fix versions. ## How was this patch tested? I manually copied and pasted the specific codes and tested separately in both Python 2 and Python 3. **Positive cases:** ``` Enter comma-separated fix version(s) [3.0.0]: # blank test (to use default) ['3.0.0'] ``` ``` Enter comma-separated fix version(s) [3.0.0,2.4.2]: # multiple default versions ['3.0.0', '2.4.2'] ``` ``` Enter comma-separated fix version(s) [3.0.0]: 2.4.1 # valid version ['2.4.1'] ``` ``` Enter comma-separated fix version(s) [3.0.0]: 3.0.0,2.4.2 # multiple valid versions ['3.0.0', '2.4.2'] ``` **Keyboard interrupt(Ctrl + c):** ``` Enter comma-separated fix version(s) [3.0.0]: ^CTraceback (most recent call last): # keyboard interrupt File "test_merge_script.py", line 45, in <module> test() File "test_merge_script.py", line 26, in test fix_versions = input("Enter comma-separated fix version(s) [%s]: " % default_fix_versions) KeyboardInterrupt ``` **Wrongly typed versions (recovered):** ``` Enter comma-separated fix version(s) [3.0.0]: 3.1 Specified version(s) [3.1] not found in the available versions, try again (or leave blank and fix manually). Enter comma-separated fix version(s) [3.0.0]: 123 Specified version(s) [123] not found in the available versions, try again (or leave blank and fix manually). Enter comma-separated fix version(s) [3.0.0]: 3.0,0 Specified version(s) [3.0, 0] not found in the available versions, try again (or leave blank and fix manually). Enter comma-separated fix version(s) [3.0.0]: damn Specified version(s) [damn] not found in the available versions, try again (or leave blank and fix manually). Enter comma-separated fix version(s) [3.0.0]: 3.0.0,2.5.2 # one invalid versions in multiple versions Specified version(s) [3.0.0, 2.5.2] not found in the available versions, try again (or leave blank and fix manually). ``` **Arbitrary exceptions in fix version parsing (recovered)** ``` Enter comma-separated fix version(s) [3.0.0]: Traceback (most recent call last): File "tmp.py", line 11, in <module> raise Exception("arbitrary exception") Exception: arbitrary exception Error setting fix version(s), try again (or leave blank and fix manually) Enter comma-separated fix version(s) [3.0.0]: Traceback (most recent call last): File "tmp.py", line 10, in <module> raise Exception("arbitrary exception") Exception: arbitrary exception Error setting fix version(s), try again (or leave blank and fix manually) Enter comma-separated fix version(s) [3.0.0]: ``` Closes #24213 from HyukjinKwon/merge_script_fix_version. Authored-by: Hyukjin Kwon <gurwls223@apache.org> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org> |
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Apache Spark
Spark is a fast and general cluster computing system for Big Data. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.
Online Documentation
You can find the latest Spark documentation, including a programming guide, on the project web page. This README file only contains basic setup instructions.
Building Spark
Spark is built using Apache Maven. To build Spark and its example programs, run:
build/mvn -DskipTests clean package
(You do not need to do this if you downloaded a pre-built package.)
You can build Spark using more than one thread by using the -T option with Maven, see "Parallel builds in Maven 3". More detailed documentation is available from the project site, at "Building Spark".
For general development tips, including info on developing Spark using an IDE, see "Useful Developer Tools".
Interactive Scala Shell
The easiest way to start using Spark is through the Scala shell:
./bin/spark-shell
Try the following command, which should return 1000:
scala> sc.parallelize(1 to 1000).count()
Interactive Python Shell
Alternatively, if you prefer Python, you can use the Python shell:
./bin/pyspark
And run the following command, which should also return 1000:
>>> sc.parallelize(range(1000)).count()
Example Programs
Spark also comes with several sample programs in the examples
directory.
To run one of them, use ./bin/run-example <class> [params]
. For example:
./bin/run-example SparkPi
will run the Pi example locally.
You can set the MASTER environment variable when running examples to submit
examples to a cluster. This can be a mesos:// or spark:// URL,
"yarn" to run on YARN, and "local" to run
locally with one thread, or "local[N]" to run locally with N threads. You
can also use an abbreviated class name if the class is in the examples
package. For instance:
MASTER=spark://host:7077 ./bin/run-example SparkPi
Many of the example programs print usage help if no params are given.
Running Tests
Testing first requires building Spark. Once Spark is built, tests can be run using:
./dev/run-tests
Please see the guidance on how to run tests for a module, or individual tests.
There is also a Kubernetes integration test, see resource-managers/kubernetes/integration-tests/README.md
A Note About Hadoop Versions
Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported storage systems. Because the protocols have changed in different versions of Hadoop, you must build Spark against the same version that your cluster runs.
Please refer to the build documentation at "Specifying the Hadoop Version and Enabling YARN" for detailed guidance on building for a particular distribution of Hadoop, including building for particular Hive and Hive Thriftserver distributions.
Configuration
Please refer to the Configuration Guide in the online documentation for an overview on how to configure Spark.
Contributing
Please review the Contribution to Spark guide for information on how to get started contributing to the project.