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Posted to reviews@spark.apache.org by marmbrus <gi...@git.apache.org> on 2016/01/07 22:55:09 UTC
[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes
GitHub user marmbrus opened a pull request:
https://github.com/apache/spark/pull/10650
[SPARK-12696] Backport Dataset Bug fixes
We've fixed a lot of bugs in master, and since this is experimental in 1.6 we should consider back porting the fixes. The only thing that is obviously risky to me is 0e07ed3, we might try to remove that.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/marmbrus/spark dataset-backports
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/10650.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 #10650
----
commit 5025da6d8cd99ac793397c8e06ba2dbefa737ea8
Author: Wenchen Fan <we...@databricks.com>
Date: 2015-12-10T07:11:13Z
[SPARK-12252][SPARK-12131][SQL] refactor MapObjects to make it less hacky
in https://github.com/apache/spark/pull/10133 we found that, we shoud ensure the children of `TreeNode` are all accessible in the `productIterator`, or the behavior will be very confusing.
In this PR, I try to fix this problem by expsing the `loopVar`.
This also fixes SPARK-12131 which is caused by the hacky `MapObjects`.
Author: Wenchen Fan <we...@databricks.com>
Closes #10239 from cloud-fan/map-objects.
commit c938a4375932fcf8cbdeefe55449798033d55bb1
Author: Wenchen Fan <we...@databricks.com>
Date: 2015-12-15T00:48:11Z
[SPARK-12274][SQL] WrapOption should not have type constraint for child
I think it was a mistake, and we have not catched it so far until https://github.com/apache/spark/pull/10260 which begin to check if the `fromRowExpression` is resolved.
Author: Wenchen Fan <we...@databricks.com>
Closes #10263 from cloud-fan/encoder.
commit 7d1d389323a0a4732f0df6d7b3af5f83a05dc5eb
Author: gatorsmile <ga...@gmail.com>
Date: 2015-12-15T02:33:45Z
[SPARK-12188][SQL][FOLLOW-UP] Code refactoring and comment correction in Dataset APIs
marmbrus This PR is to address your comment. Thanks for your review!
Author: gatorsmile <ga...@gmail.com>
Closes #10214 from gatorsmile/followup12188.
commit 862cb1281be8e2b147634a6bbb70c1ab0c0061f0
Author: Nong Li <no...@databricks.com>
Date: 2015-12-16T00:55:58Z
[SPARK-12271][SQL] Improve error message when Dataset.as[ ] has incompatible schemas.
Author: Nong Li <no...@databricks.com>
Closes #10260 from nongli/spark-11271.
commit d62701d1782df0c79bf9341ad988551175d1eb2c
Author: Wenchen Fan <we...@databricks.com>
Date: 2015-12-16T21:18:56Z
[SPARK-12320][SQL] throw exception if the number of fields does not line up for Tuple encoder
Author: Wenchen Fan <we...@databricks.com>
Closes #10293 from cloud-fan/err-msg.
commit 1a12f086acc61de0aa0e947d50bcab93ae235fed
Author: gatorsmile <ga...@gmail.com>
Date: 2015-12-16T21:22:34Z
[SPARK-12164][SQL] Decode the encoded values and then display
Based on the suggestions from marmbrus cloud-fan in https://github.com/apache/spark/pull/10165 , this PR is to print the decoded values(user objects) in `Dataset.show`
```scala
implicit val kryoEncoder = Encoders.kryo[KryoClassData]
val ds = Seq(KryoClassData("a", 1), KryoClassData("b", 2), KryoClassData("c", 3)).toDS()
ds.show(20, false);
```
The current output is like
```
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|value |
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|[1, 0, 111, 114, 103, 46, 97, 112, 97, 99, 104, 101, 46, 115, 112, 97, 114, 107, 46, 115, 113, 108, 46, 75, 114, 121, 111, 67, 108, 97, 115, 115, 68, 97, 116, -31, 1, 1, -126, 97, 2]|
|[1, 0, 111, 114, 103, 46, 97, 112, 97, 99, 104, 101, 46, 115, 112, 97, 114, 107, 46, 115, 113, 108, 46, 75, 114, 121, 111, 67, 108, 97, 115, 115, 68, 97, 116, -31, 1, 1, -126, 98, 4]|
|[1, 0, 111, 114, 103, 46, 97, 112, 97, 99, 104, 101, 46, 115, 112, 97, 114, 107, 46, 115, 113, 108, 46, 75, 114, 121, 111, 67, 108, 97, 115, 115, 68, 97, 116, -31, 1, 1, -126, 99, 6]|
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
```
After the fix, it will be like the below if and only if the users override the `toString` function in the class `KryoClassData`
```scala
override def toString: String = s"KryoClassData($a, $b)"
```
```
+-------------------+
|value |
+-------------------+
|KryoClassData(a, 1)|
|KryoClassData(b, 2)|
|KryoClassData(c, 3)|
+-------------------+
```
If users do not override the `toString` function, the results will be like
```
+---------------------------------------+
|value |
+---------------------------------------+
|org.apache.spark.sql.KryoClassData68ef|
|org.apache.spark.sql.KryoClassData6915|
|org.apache.spark.sql.KryoClassData693b|
+---------------------------------------+
```
Question: Should we add another optional parameter in the function `show`? It will decide if the function `show` will display the hex values or the object values?
Author: gatorsmile <ga...@gmail.com>
Closes #10215 from gatorsmile/showDecodedValue.
commit 0e07ed3d3e10f148a2be3fe2d03c8427ffd8a9b1
Author: Wenchen Fan <we...@databricks.com>
Date: 2015-12-21T20:47:07Z
[SPARK-12321][SQL] JSON format for TreeNode (use reflection)
An alternative solution for https://github.com/apache/spark/pull/10295 , instead of implementing json format for all logical/physical plans and expressions, use reflection to implement it in `TreeNode`.
Here I use pre-order traversal to flattern a plan tree to a plan list, and add an extra field `num-children` to each plan node, so that we can reconstruct the tree from the list.
example json:
logical plan tree:
```
[ {
"class" : "org.apache.spark.sql.catalyst.plans.logical.Sort",
"num-children" : 1,
"order" : [ [ {
"class" : "org.apache.spark.sql.catalyst.expressions.SortOrder",
"num-children" : 1,
"child" : 0,
"direction" : "Ascending"
}, {
"class" : "org.apache.spark.sql.catalyst.expressions.AttributeReference",
"num-children" : 0,
"name" : "i",
"dataType" : "integer",
"nullable" : true,
"metadata" : { },
"exprId" : {
"id" : 10,
"jvmId" : "cd1313c7-3f66-4ed7-a320-7d91e4633ac6"
},
"qualifiers" : [ ]
} ] ],
"global" : false,
"child" : 0
}, {
"class" : "org.apache.spark.sql.catalyst.plans.logical.Project",
"num-children" : 1,
"projectList" : [ [ {
"class" : "org.apache.spark.sql.catalyst.expressions.Alias",
"num-children" : 1,
"child" : 0,
"name" : "i",
"exprId" : {
"id" : 10,
"jvmId" : "cd1313c7-3f66-4ed7-a320-7d91e4633ac6"
},
"qualifiers" : [ ]
}, {
"class" : "org.apache.spark.sql.catalyst.expressions.Add",
"num-children" : 2,
"left" : 0,
"right" : 1
}, {
"class" : "org.apache.spark.sql.catalyst.expressions.AttributeReference",
"num-children" : 0,
"name" : "a",
"dataType" : "integer",
"nullable" : true,
"metadata" : { },
"exprId" : {
"id" : 0,
"jvmId" : "cd1313c7-3f66-4ed7-a320-7d91e4633ac6"
},
"qualifiers" : [ ]
}, {
"class" : "org.apache.spark.sql.catalyst.expressions.Literal",
"num-children" : 0,
"value" : "1",
"dataType" : "integer"
} ], [ {
"class" : "org.apache.spark.sql.catalyst.expressions.Alias",
"num-children" : 1,
"child" : 0,
"name" : "j",
"exprId" : {
"id" : 11,
"jvmId" : "cd1313c7-3f66-4ed7-a320-7d91e4633ac6"
},
"qualifiers" : [ ]
}, {
"class" : "org.apache.spark.sql.catalyst.expressions.Multiply",
"num-children" : 2,
"left" : 0,
"right" : 1
}, {
"class" : "org.apache.spark.sql.catalyst.expressions.AttributeReference",
"num-children" : 0,
"name" : "a",
"dataType" : "integer",
"nullable" : true,
"metadata" : { },
"exprId" : {
"id" : 0,
"jvmId" : "cd1313c7-3f66-4ed7-a320-7d91e4633ac6"
},
"qualifiers" : [ ]
}, {
"class" : "org.apache.spark.sql.catalyst.expressions.Literal",
"num-children" : 0,
"value" : "2",
"dataType" : "integer"
} ] ],
"child" : 0
}, {
"class" : "org.apache.spark.sql.catalyst.plans.logical.LocalRelation",
"num-children" : 0,
"output" : [ [ {
"class" : "org.apache.spark.sql.catalyst.expressions.AttributeReference",
"num-children" : 0,
"name" : "a",
"dataType" : "integer",
"nullable" : true,
"metadata" : { },
"exprId" : {
"id" : 0,
"jvmId" : "cd1313c7-3f66-4ed7-a320-7d91e4633ac6"
},
"qualifiers" : [ ]
} ] ],
"data" : [ ]
} ]
```
Author: Wenchen Fan <we...@databricks.com>
Closes #10311 from cloud-fan/toJson-reflection.
commit b8a8ba40fcebbe37c7ffaeac91e0dd90b7a072a3
Author: Cheng Lian <li...@databricks.com>
Date: 2015-12-22T11:41:44Z
[SPARK-12371][SQL] Runtime nullability check for NewInstance
This PR adds a new expression `AssertNotNull` to ensure non-nullable fields of products and case classes don't receive null values at runtime.
Author: Cheng Lian <li...@databricks.com>
Closes #10331 from liancheng/dataset-nullability-check.
commit 36adc41a57284f58449e8df68e50d9baf7a042a8
Author: Cheng Lian <li...@databricks.com>
Date: 2015-12-23T02:21:00Z
[SPARK-12478][SQL] Bugfix: Dataset fields of product types can't be null
When creating extractors for product types (i.e. case classes and tuples), a null check is missing, thus we always assume input product values are non-null.
This PR adds a null check in the extractor expression for product types. The null check is stripped off for top level product fields, which are mapped to the outermost `Row`s, since they can't be null.
Thanks cloud-fan for helping investigating this issue!
Author: Cheng Lian <li...@databricks.com>
Closes #10431 from liancheng/spark-12478.top-level-null-field.
commit 7ca2d78b2e1d03ed1ffd5855c538529835a8c2c0
Author: gatorsmile <ga...@gmail.com>
Date: 2015-12-30T06:28:59Z
[SPARK-12564][SQL] Improve missing column AnalysisException
```
org.apache.spark.sql.AnalysisException: cannot resolve 'value' given input columns text;
```
lets put a `:` after `columns` and put the columns in `[]` so that they match the toString of DataFrame.
Author: gatorsmile <ga...@gmail.com>
Closes #10518 from gatorsmile/improveAnalysisExceptionMsg.
commit d42f9a62f61ee602ed56274e44254f91f9ea05a5
Author: Wenchen Fan <we...@databricks.com>
Date: 2015-12-30T18:56:08Z
[SPARK-12495][SQL] use true as default value for propagateNull in NewInstance
Most of cases we should propagate null when call `NewInstance`, and so far there is only one case we should stop null propagation: create product/java bean. So I think it makes more sense to propagate null by dafault.
This also fixes a bug when encode null array/map, which is firstly discovered in https://github.com/apache/spark/pull/10401
Author: Wenchen Fan <we...@databricks.com>
Closes #10443 from cloud-fan/encoder.
commit 80773f5f6d6f792989364633ccf9c6589a6c6372
Author: Liang-Chi Hsieh <vi...@gmail.com>
Date: 2016-01-01T07:48:05Z
[SPARK-11743][SQL] Move the test for arrayOfUDT
A following pr for #9712. Move the test for arrayOfUDT.
Author: Liang-Chi Hsieh <vi...@gmail.com>
Closes #10538 from viirya/move-udt-test.
commit b6295c105406cfde46275ab8fef31fc57d1d86ba
Author: Liang-Chi Hsieh <vi...@gmail.com>
Date: 2016-01-05T18:19:56Z
[SPARK-12438][SQL] Add SQLUserDefinedType support for encoder
JIRA: https://issues.apache.org/jira/browse/SPARK-12438
ScalaReflection lacks the support of SQLUserDefinedType. We should add it.
Author: Liang-Chi Hsieh <vi...@gmail.com>
Closes #10390 from viirya/encoder-udt.
commit 87fc0ffb67e6538b2b850e0fd36ba6e2c63fc549
Author: Liang-Chi Hsieh <vi...@gmail.com>
Date: 2016-01-05T20:33:21Z
[SPARK-12439][SQL] Fix toCatalystArray and MapObjects
JIRA: https://issues.apache.org/jira/browse/SPARK-12439
In toCatalystArray, we should look at the data type returned by dataTypeFor instead of silentSchemaFor, to determine if the element is native type. An obvious problem is when the element is Option[Int] class, catalsilentSchemaFor will return Int, then we will wrongly recognize the element is native type.
There is another problem when using Option as array element. When we encode data like Seq(Some(1), Some(2), None) with encoder, we will use MapObjects to construct an array for it later. But in MapObjects, we don't check if the return value of lambdaFunction is null or not. That causes a bug that the decoded data for Seq(Some(1), Some(2), None) would be Seq(1, 2, -1), instead of Seq(1, 2, null).
Author: Liang-Chi Hsieh <vi...@gmail.com>
Closes #10391 from viirya/fix-catalystarray.
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by marmbrus <gi...@git.apache.org>.
Github user marmbrus commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169854996
test this please
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169873544
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169873468
**[Test build #48991 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/48991/consoleFull)** for PR 10650 at commit [`87fc0ff`](https://github.com/apache/spark/commit/87fc0ffb67e6538b2b850e0fd36ba6e2c63fc549).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169821953
**[Test build #48972 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/48972/consoleFull)** for PR 10650 at commit [`87fc0ff`](https://github.com/apache/spark/commit/87fc0ffb67e6538b2b850e0fd36ba6e2c63fc549).
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169857832
**[Test build #48991 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/48991/consoleFull)** for PR 10650 at commit [`87fc0ff`](https://github.com/apache/spark/commit/87fc0ffb67e6538b2b850e0fd36ba6e2c63fc549).
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by liancheng <gi...@git.apache.org>.
Github user liancheng commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-170150479
LGTM. Double checked 0e07ed3, it's quite self contained and doesn't affect query execution code path. Should be safe to backport (I think fixing all the merge conflicts might be riskier). All other commits also look good.
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by marmbrus <gi...@git.apache.org>.
Github user marmbrus closed the pull request at:
https://github.com/apache/spark/pull/10650
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169847122
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by marmbrus <gi...@git.apache.org>.
Github user marmbrus commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169844423
test this please
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes
Posted by AmplabJenkins <gi...@git.apache.org>.
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by AmplabJenkins <gi...@git.apache.org>.
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by marmbrus <gi...@git.apache.org>.
Github user marmbrus commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-170152766
Thanks, merging to branch-1.6
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169823762
**[Test build #48972 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/48972/consoleFull)** for PR 10650 at commit [`87fc0ff`](https://github.com/apache/spark/commit/87fc0ffb67e6538b2b850e0fd36ba6e2c63fc549).
* This patch **fails to build**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by rxin <gi...@git.apache.org>.
Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169899011
Changes LGTM
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169847116
**[Test build #48989 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/48989/consoleFull)** for PR 10650 at commit [`87fc0ff`](https://github.com/apache/spark/commit/87fc0ffb67e6538b2b850e0fd36ba6e2c63fc549).
* This patch **fails to build**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169845842
**[Test build #48989 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/48989/consoleFull)** for PR 10650 at commit [`87fc0ff`](https://github.com/apache/spark/commit/87fc0ffb67e6538b2b850e0fd36ba6e2c63fc549).
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[GitHub] spark pull request: [SPARK-12696] Backport Dataset Bug fixes to 1....
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/10650#issuecomment-169873543
Merged build finished. Test PASSed.
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