Open issues

Integration Testing for different variation of Spark
SW-179
Add support for Spark Dynamic Allocation
SW-556
Test Sparkling Water on Standalone Cluster
SW-106
Sparkling shell: newly created classes are not visible by remote nodes
SW-36
Add Tests Covering Scenarios with XGBoost and Offset Column
SW-1852
Remove deprecated methods in RSparkling, from release 3.30 only instance methods should be used
SW-1850
Automatically document Sparkling Water Algo API
SW-1847
Start Compiling Sparkling Water with Scala 2.12
SW-1846
Replace Apache Http Client with a Client Supporting Request Streaming
SW-1844
Read Chunks via REST API
SW-1840
Sparkling water hangs on asH2OFrame
SW-1834
Removed Deprecated The r2stopping Parameter on GBM and DRF
SW-1833
Support h2o3 mojo prediction in rsparkling
SW-1830
Remove deprecated support for passing username and password in RSparkling in favor of the spark options
SW-1827
Switch RSparkling in internal backend to client-less approach by default
SW-1825
Switch RSparkling in external backend to client-less approach by default
SW-1824
Remove deprecated r2stopping arameter on GBM and DRF
SW-1819
Switch PySparkling in internal backend to client-less approach by default
SW-1818
RSparkling in cran should be dummy code to point to our rsparkling in custom repo
SW-1790
Remove deprecated support for passing auth credentials via H2OContext in PySparkling
SW-1786
Change Spark DataFrame to H2OFrame Conversion to Implicitly Convert String Columns to Categoricals
SW-1779
MOJO2: Expose option to have "strict" data mode in MOJOFrame creation
SW-1778
Add possibility to start multiple external H2O backends in automatic mode in client-less approach
SW-1763
Remove support for Spark 2.1
SW-1753
Add test for preemption during as_h2o_frame on high concurrency Databricks clusters
SW-1752
Deprecate Spark 2.1
SW-1751
Ensure that multi-line strings in Python can be formatted in a similar way as it is in Scala
SW-1742
Replace External H2O writer & reader by rest api
SW-1728
What should be the sparkling water instance executor/driver memory suggestions based on dataset size on disk
SW-1727
Switch PySparkling in external backend to client-less approach by default
SW-1715
Add sparkling water version info in the h2o logs
SW-1709
Expose offset_column in XGBoost
SW-1686
Create scoring package for pysparkling
SW-1679
Pass params to h2o_context
SW-1673
Structure Contributions in the 'detailed_prediction' Column Better
SW-1668
Revisit PySparkling Water Initializer - adding sparkling-water.jar to classpath has non-deterministic behavior
SW-1665
pysparkling numpy compatibility on Azure Databricks
SW-1663
as_h2o_frame is slow in external mode
SW-1657
Expose H2O SVM into Sparkling Water Algorithm API
SW-1652
SparklingWater forms only H2O cluster on Azure only with one node
SW-1650
GridSearch Should Reference Hyper Parameters with SW Names
SW-1608
Test setting non-default values on PySparkling Algos via setters and via construtor
SW-1590
Deprecate Sparkling Water SVM in favor of H2O one
SW-1589
H2OGBM in pyspark
SW-1579
Sparkling water fails to detect newer version of colorama
SW-1569
Have automatic kubernetes tests
SW-1566
Upload docker images to docker hub as part of release
SW-1563
Support for Kubernetes
SW-1562
Cloud up of SW fails on EMR
SW-1559
get-extended-h2o script does not work for nightlies
SW-1544
issue 1 of 166

Integration Testing for different variation of Spark

Description

We need to test for:

  • HDP (different version)

  • CDH5.7, CDH5.8

  • EMR

The tests have to

  • be automatic

  • be defined at a single space - see (Jenkins Pipelines)

Assignee

Michal Malohlava

Reporter

Michal Malohlava

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