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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2015/06/19 00:22:00 UTC
[jira] [Updated] (SPARK-7536) Audit MLlib Python API for 1.4
[ https://issues.apache.org/jira/browse/SPARK-7536?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley updated SPARK-7536:
-------------------------------------
Description:
For new public APIs added to MLlib, we need to check the generated HTML doc and compare the Scala & Python versions. We need to track:
* Inconsistency: Do class/method/parameter names match? SPARK-7667
* Docs: Is the Python doc missing or just a stub? We want the Python doc to be as complete as the Scala doc. [SPARK-7666], [SPARK-6173]
* API breaking changes: These should be very rare but are occasionally either necessary (intentional) or accidental. These must be recorded and added in the Migration Guide for this release. SPARK-7665
** Note: If the API change is for an Alpha/Experimental/DeveloperApi component, please note that as well.
* Missing classes/methods/parameters: We should create to-do JIRAs for functionality missing from Python.
** classification
*** StreamingLogisticRegressionWithSGD SPARK-7633
** clustering
*** GaussianMixture SPARK-6258
*** LDA SPARK-6259
*** Power Iteration Clustering SPARK-5962
*** StreamingKMeans SPARK-4118
** evaluation
*** MultilabelMetrics SPARK-6094
** feature
*** ElementwiseProduct SPARK-7605
*** PCA SPARK-7604
** linalg
*** Distributed linear algebra SPARK-6100
** pmml.export SPARK-7638
** regression
*** StreamingLinearRegressionWithSGD SPARK-4127
** stat
*** KernelDensity SPARK-7639
** util
*** MLUtils SPARK-6263
was:
For new public APIs added to MLlib, we need to check the generated HTML doc and compare the Scala & Python versions. We need to track:
* Inconsistency: Do class/method/parameter names match? SPARK-7667
* Docs: Is the Python doc missing or just a stub? We want the Python doc to be as complete as the Scala doc. SPARK-7666
* API breaking changes: These should be very rare but are occasionally either necessary (intentional) or accidental. These must be recorded and added in the Migration Guide for this release. SPARK-7665
** Note: If the API change is for an Alpha/Experimental/DeveloperApi component, please note that as well.
* Missing classes/methods/parameters: We should create to-do JIRAs for functionality missing from Python.
** classification
*** StreamingLogisticRegressionWithSGD SPARK-7633
** clustering
*** GaussianMixture SPARK-6258
*** LDA SPARK-6259
*** Power Iteration Clustering SPARK-5962
*** StreamingKMeans SPARK-4118
** evaluation
*** MultilabelMetrics SPARK-6094
** feature
*** ElementwiseProduct SPARK-7605
*** PCA SPARK-7604
** linalg
*** Distributed linear algebra SPARK-6100
** pmml.export SPARK-7638
** regression
*** StreamingLinearRegressionWithSGD SPARK-4127
** stat
*** KernelDensity SPARK-7639
** util
*** MLUtils SPARK-6263
> Audit MLlib Python API for 1.4
> ------------------------------
>
> Key: SPARK-7536
> URL: https://issues.apache.org/jira/browse/SPARK-7536
> Project: Spark
> Issue Type: Sub-task
> Components: MLlib, PySpark
> Reporter: Joseph K. Bradley
> Assignee: Yanbo Liang
>
> For new public APIs added to MLlib, we need to check the generated HTML doc and compare the Scala & Python versions. We need to track:
> * Inconsistency: Do class/method/parameter names match? SPARK-7667
> * Docs: Is the Python doc missing or just a stub? We want the Python doc to be as complete as the Scala doc. [SPARK-7666], [SPARK-6173]
> * API breaking changes: These should be very rare but are occasionally either necessary (intentional) or accidental. These must be recorded and added in the Migration Guide for this release. SPARK-7665
> ** Note: If the API change is for an Alpha/Experimental/DeveloperApi component, please note that as well.
> * Missing classes/methods/parameters: We should create to-do JIRAs for functionality missing from Python.
> ** classification
> *** StreamingLogisticRegressionWithSGD SPARK-7633
> ** clustering
> *** GaussianMixture SPARK-6258
> *** LDA SPARK-6259
> *** Power Iteration Clustering SPARK-5962
> *** StreamingKMeans SPARK-4118
> ** evaluation
> *** MultilabelMetrics SPARK-6094
> ** feature
> *** ElementwiseProduct SPARK-7605
> *** PCA SPARK-7604
> ** linalg
> *** Distributed linear algebra SPARK-6100
> ** pmml.export SPARK-7638
> ** regression
> *** StreamingLinearRegressionWithSGD SPARK-4127
> ** stat
> *** KernelDensity SPARK-7639
> ** util
> *** MLUtils SPARK-6263
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