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https://issues.apache.org/jira/browse/FLINK-3656?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15548219#comment-15548219
]
ASF GitHub Bot commented on FLINK-3656:
---------------------------------------
GitHub user twalthr opened a pull request:
https://github.com/apache/flink/pull/2595
[FLINK-3656] [table] Test base for logical unit testing
This PR introduces a test base for logical unit testing. It could replace
most of current ITCases as it checks if the API is correctly translated into
`DataSet`/`DataStream` RelNodes. The translation to DataSet/DataStream
operators should be tested separately by unit tests for those (e.g.
`DataSetCalcTest`, `DataSetJoinTest` etc.).
Here is an example how a JointITCase could be converted:
```scala
@Test
def testJoin(): Unit = {
val util = batchTestUtil()
val in1 = util.addTable[(Int, Long, String)]("Left", 'a, 'b, 'c)
val in2 = util.addTable[(Int, Long, Int, String, Long)]("Right", 'd, 'e,
'f, 'g, 'h)
val table = in1.join(in2).where("b === e").select("c, g")
val expected = unaryNode(
"DataSetCalc",
binaryNode(
"DataSetJoin",
batchTableNode(0),
batchTableNode(1),
term("where", "=(b, e)"),
term("join", "a", "b", "c", "d", "e", "f", "g", "h")
),
term("joinType", "Join")
)
util.verifyTable(table, expected)
}
```
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/twalthr/flink FLINK-3656_UNIT_TEST_UTILS
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/flink/pull/2595.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #2595
----
commit c384628cd1f48f993973bb2e831720a98d55ca16
Author: twalthr <twal...@apache.org>
Date: 2016-10-04T16:32:52Z
[FLINK-3656] [table] Test base for logical unit testing
----
> Rework Table API tests
> ----------------------
>
> Key: FLINK-3656
> URL: https://issues.apache.org/jira/browse/FLINK-3656
> Project: Flink
> Issue Type: Improvement
> Components: Table API & SQL
> Reporter: Vasia Kalavri
> Labels: starter
>
> The Table API tests are very inefficient. At the moment It is mostly
> end-to-end integration tests, often testing the same functionality several
> times (Java/Scala, DataSet/DataStream).
> We should look into how we can rework the Table API tests such that:
> - long-running integration tests are converted into faster unit tests
> - common parts of DataSet and DataStream are only tested once
> - common parts of Java and Scala Table APIs are only tested once
> - duplicate tests are completely removed
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