JIRA issue [link](https://issues.apache.org/jira/browse/SPARK-7663).
We should check the model size of word2vec, to prevent the unexpected empty.
CC srowen.
Author: Xusen Yin <yinxusen@gmail.com>
Closes#6228 from yinxusen/SPARK-7663 and squashes the following commits:
21770c5 [Xusen Yin] check the vocab size
54ae63e [Xusen Yin] add requirement for word2vec model
follow up for #5806
Author: scwf <wangfei1@huawei.com>
Closes#6164 from scwf/FunctionRegistry and squashes the following commits:
15e6697 [scwf] use catalogconf in FunctionRegistry
The documentation for BlockMatrix should come after RowMatrix, IndexedRowMatrix, and CoordinateMatrix, as BlockMatrix references the later three types, and RowMatrix is considered the "basic" distributed matrix. This will improve comprehensibility of the "Distributed matrix" section, especially for the new reader.
Author: Mike Dusenberry <dusenberrymw@gmail.com>
Closes#6270 from dusenberrymw/Reorder_MLlib_Data_Types_Distributed_matrix_docs and squashes the following commits:
6313bab [Mike Dusenberry] The documentation for BlockMatrix should come after RowMatrix, IndexedRowMatrix, and CoordinateMatrix, as BlockMatrix references the later three types, and RowMatrix is considered the "basic" distributed matrix. This will improve comprehensibility of the "Distributed matrix" section, especially for the new reader.
This is a small fix. But it is important for amazon users because as the ticket states, "spark-ec2 can't handle clusters with > 100 nodes" now.
Author: alyaxey <oleksii.sliusarenko@grammarly.com>
Closes#6267 from alyaxey/ec2_100_nodes_fix and squashes the following commits:
1e0d747 [alyaxey] [SPARK-6246] fixed support for more than 100 nodes
```
select explode(map(value, key)) from src;
```
Throws exception
```
org.apache.spark.sql.AnalysisException: The number of aliases supplied in the AS clause does not match the number of columns output by the UDTF expected 2 aliases but got _c0 ;
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:38)
at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:43)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGenerate$.org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveGenerate$$makeGeneratorOutput(Analyzer.scala:605)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGenerate$$anonfun$apply$16$$anonfun$22.apply(Analyzer.scala:562)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGenerate$$anonfun$apply$16$$anonfun$22.apply(Analyzer.scala:548)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGenerate$$anonfun$apply$16.applyOrElse(Analyzer.scala:548)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveGenerate$$anonfun$apply$16.applyOrElse(Analyzer.scala:538)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:222)
```
Author: Cheng Hao <hao.cheng@intel.com>
Closes#6178 from chenghao-intel/explode and squashes the following commits:
916fbe9 [Cheng Hao] add more strict rules for TGF alias
5c3f2c5 [Cheng Hao] fix bug in unit test
e1d93ab [Cheng Hao] Add more unit test
19db09e [Cheng Hao] resolve names for generator in projection
cc rxin, please take a quick look, I'm working on tests.
Author: Davies Liu <davies@databricks.com>
Closes#6238 from davies/readwrite and squashes the following commits:
c7200eb [Davies Liu] update tests
9cbf01b [Davies Liu] Merge branch 'master' of github.com:apache/spark into readwrite
f0c5a04 [Davies Liu] use sqlContext.read.load
5f68bc8 [Davies Liu] update tests
6437e9a [Davies Liu] Merge branch 'master' of github.com:apache/spark into readwrite
bcc6668 [Davies Liu] add reader amd writer API in Python
CC jkbradley.
JIRA [issue](https://issues.apache.org/jira/browse/SPARK-7586).
Author: Xusen Yin <yinxusen@gmail.com>
Closes#6181 from yinxusen/SPARK-7586 and squashes the following commits:
77014c5 [Xusen Yin] comment fix
57a4c07 [Xusen Yin] small fix for docs
1178c8f [Xusen Yin] remove the correctness check in java suite
1c3f389 [Xusen Yin] delete sbt commit
1af152b [Xusen Yin] check python example code
1b5369e [Xusen Yin] add docs of word2vec
Visibility rules for static members are different in Scala and Java, and this case requires an explicit static import. Even though these are Java files, they are run through scaladoc, which enforces Scala rules.
Also reverted the commit that reverts the upgrade to 2.11.6
Author: Iulian Dragos <jaguarul@gmail.com>
Closes#6260 from dragos/issue/scaladoc-false-error and squashes the following commits:
f2e998e [Iulian Dragos] Revert "[HOTFIX] Revert "[SPARK-7092] Update spark scala version to 2.11.6""
0bad052 [Iulian Dragos] Fix scaladoc faux-error.
Changed shared param HasSeed to have default based on hashCode of class name, instead of random number.
Also, removed fixed random seeds from Word2Vec and ALS.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#6251 from jkbradley/scala-fixed-seed and squashes the following commits:
0e37184 [Joseph K. Bradley] Fixed Word2VecSuite, ALSSuite in spark.ml to use original fixed random seeds
678ec3a [Joseph K. Bradley] Removed fixed random seeds from Word2Vec and ALS. Changed shared param HasSeed to have default based on hashCode of class name, instead of random number.
Made Model.parent transient. Added Model.hasParent to test for null parent
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5914 from jkbradley/parent-optional and squashes the following commits:
d501774 [Joseph K. Bradley] Made Model.parent transient. Added Model.hasParent to test for null parent
The change per SPARK-4397 makes implicit objects in SparkContext to be found by the compiler automatically. So that we don't need to import the o.a.s.SparkContext._ explicitly any more and can remove some statements around the "implicit conversions" from the latest Programming Guides (1.3.0 and higher)
Author: Dice <poleon.kd@gmail.com>
Closes#6234 from daisukebe/patch-1 and squashes the following commits:
b77ecd9 [Dice] fix a typo
45dfcd3 [Dice] rewording per Sean's advice
a094bcf [Dice] Adding a note for users on any previous releases
a29be5f [Dice] Updating Programming Guides per SPARK-4397
There excludes are unnecessary for 1.3 because the changes were made in 1.4.x.
Author: Xiangrui Meng <meng@databricks.com>
Closes#6254 from mengxr/SPARK-7681-mima and squashes the following commits:
7f0cea0 [Xiangrui Meng] remove mima excludes for 1.3
https://issues.apache.org/jira/browse/SPARK-7723
Author: Saleem Ansari <tuxdna@gmail.com>
Closes#6258 from tuxdna/master and squashes the following commits:
2bb5a42 [Saleem Ansari] Merge branch 'master' into mllib-pipeline
e39db9c [Saleem Ansari] Fix string interpolation in pipeline examples
Just a few minor fixes in the guide, so a new JIRA issue was not created per the guidelines.
Author: Mike Dusenberry <dusenberrymw@gmail.com>
Closes#6240 from dusenberrymw/Fix_Programming_Guide_Typos and squashes the following commits:
ffa76eb [Mike Dusenberry] Fixing a few basic typos in the Programming Guide.
JIRA [here](https://issues.apache.org/jira/browse/SPARK-7581).
CC jkbradley
Author: Xusen Yin <yinxusen@gmail.com>
Closes#6113 from yinxusen/SPARK-7581 and squashes the following commits:
1a7d80d [Xusen Yin] merge with master
892a8e9 [Xusen Yin] fix python 3 compatibility
ec935bf [Xusen Yin] small fix
3e9fa1d [Xusen Yin] delete note
69fcf85 [Xusen Yin] simplify and add python example
81d21dc [Xusen Yin] add programming guide for Polynomial Expansion
40babfb [Xusen Yin] add java test suite for PolynomialExpansion
In `DataFrame.describe()`, the `count` aggregate produces an integer, the `avg` and `stdev` aggregates produce doubles, and `min` and `max` aggregates can produce varying types depending on what type of column they're applied to. As a result, we should cast all aggregate results to String so that `describe()`'s output types match its declared output schema.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#6218 from JoshRosen/SPARK-7687 and squashes the following commits:
146b615 [Josh Rosen] Fix R test.
2974bd5 [Josh Rosen] Cast to string type instead
f206580 [Josh Rosen] Cast to double to fix SPARK-7687
307ecbf [Josh Rosen] Add failing regression test for SPARK-7687
This PR is based on #6081, thanks adrian-wang.
Closes#6081
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: Davies Liu <davies@databricks.com>
Closes#6230 from davies/range and squashes the following commits:
d3ce5fe [Davies Liu] add tests
789eda5 [Davies Liu] add range() in Python
4590208 [Davies Liu] Merge commit 'refs/pull/6081/head' of github.com:apache/spark into range
cbf5200 [Daoyuan Wang] let's add python support in a separate PR
f45e3b2 [Daoyuan Wang] remove redundant toLong
617da76 [Daoyuan Wang] fix safe marge for corner cases
867c417 [Daoyuan Wang] fix
13dbe84 [Daoyuan Wang] update
bd998ba [Daoyuan Wang] update comments
d3a0c1b [Daoyuan Wang] add range api()
JIRA: https://issues.apache.org/jira/browse/SPARK-7681
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#6209 from viirya/sparsevector_gemv and squashes the following commits:
ce0bb8b [Liang-Chi Hsieh] Still need to scal y when beta is 0.0 because it clears out y.
b890e63 [Liang-Chi Hsieh] Do not delete multiply for DenseVector.
57a8c1e [Liang-Chi Hsieh] Add MimaExcludes for v1.4.
458d1ae [Liang-Chi Hsieh] List DenseMatrix.multiply and SparseMatrix.multiply to MimaExcludes too.
054f05d [Liang-Chi Hsieh] Fix scala style.
410381a [Liang-Chi Hsieh] Address comments. Make Matrix.multiply more generalized.
4616696 [Liang-Chi Hsieh] Add support for SparseVector with SparseMatrix.
5d6d07a [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into sparsevector_gemv
c069507 [Liang-Chi Hsieh] Add SparseVector support for gemv with DenseMatrix.
- Updated Kinesis examples to use stable API
- Cleaned up comments, etc.
- Renamed KinesisWordCountProducerASL to KinesisWordProducerASL
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#6249 from tdas/kinesis-examples and squashes the following commits:
7cc307b [Tathagata Das] More tweaks
f080872 [Tathagata Das] More cleanup
841987f [Tathagata Das] Small update
011cbe2 [Tathagata Das] More fixes
b0d74f9 [Tathagata Das] Updated examples.
PR per [SPARK-7621](https://issues.apache.org/jira/browse/SPARK-7621), which makes both `KafkaReceiver` and `ReliableKafkaReceiver` report its errors to the `ReceiverTracker`, which in turn will add the events to the bus to fire off any registered `StreamingListener`s.
Author: jerluc <jeremyalucas@gmail.com>
Closes#6204 from jerluc/master and squashes the following commits:
82439a5 [jerluc] [SPARK-7621] [STREAMING] Report Kafka errors to StreamingListeners
A follow-up to #6244.
Author: Michael Armbrust <michael@databricks.com>
Closes#6247 from marmbrus/fixOrcTests and squashes the following commits:
e39ee1b [Michael Armbrust] [SQL] Fix serializability of ORC table scan
this fix is to solve one issue found in lz4 1.2.0, which caused core dump in Spark Core with IBM JDK. that issue is fixed in lz4 1.3.0 version.
Author: Jihong MA <linlin200605@gmail.com>
Closes#6226 from JihongMA/SPARK-7063-1 and squashes the following commits:
0cca781 [Jihong MA] SPARK-7063
4559ed5 [Jihong MA] SPARK-7063
daa520f [Jihong MA] SPARK-7063 upgrade lz4 jars
71738ee [Jihong MA] Merge remote-tracking branch 'upstream/master'
dfaa971 [Jihong MA] SPARK-7265 minor fix of the content
ace454d [Jihong MA] SPARK-7265 take out PySpark on YARN limitation
9ea0832 [Jihong MA] Merge remote-tracking branch 'upstream/master'
d5bf3f5 [Jihong MA] Merge remote-tracking branch 'upstream/master'
7b842e6 [Jihong MA] Merge remote-tracking branch 'upstream/master'
9c84695 [Jihong MA] SPARK-7265 address review comment
a399aa6 [Jihong MA] SPARK-7265 Improving documentation for Spark SQL Hive support
This is similar to #5999, but for streaming. Roughly 200 lines are tests.
One thing to note here is that we already do some kind of scoping thing for call sites, so this patch adds the new RDD operation scoping logic in the same place. Also, this patch adds a `try finally` block to set the relevant variables in a safer way.
tdas zsxwing
------------------------
**Before**
<img src="https://cloud.githubusercontent.com/assets/2133137/7625996/d88211b8-f9b4-11e4-90b9-e11baa52d6d7.png" width="450px"/>
--------------------------
**After**
<img src="https://cloud.githubusercontent.com/assets/2133137/7625997/e0878f8c-f9b4-11e4-8df3-7dd611b13c87.png" width="650px"/>
Author: Andrew Or <andrew@databricks.com>
Closes#6034 from andrewor14/dag-viz-streaming and squashes the following commits:
932a64a [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
e685df9 [Andrew Or] Rename createRDDWith
84d0656 [Andrew Or] Review feedback
697c086 [Andrew Or] Fix tests
53b9936 [Andrew Or] Set scopes for foreachRDD properly
1881802 [Andrew Or] Refactor DStream scope names again
af4ba8d [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
fd07d22 [Andrew Or] Make MQTT lower case
f6de871 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
0ca1801 [Andrew Or] Remove a few unnecessary withScopes on aliases
fa4e5fb [Andrew Or] Pass in input stream name rather than defining it from within
1af0b0e [Andrew Or] Fix style
074c00b [Andrew Or] Review comments
d25a324 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
e4a93ac [Andrew Or] Fix tests?
25416dc [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
9113183 [Andrew Or] Add tests for DStream scopes
b3806ab [Andrew Or] Fix test
bb80bbb [Andrew Or] Fix MIMA?
5c30360 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
5703939 [Andrew Or] Rename operations that create InputDStreams
7c4513d [Andrew Or] Group RDDs by DStream operations and batches
bf0ab6e [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
05c2676 [Andrew Or] Wrap many more methods in withScope
c121047 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
65ef3e9 [Andrew Or] Fix NPE
a0d3263 [Andrew Or] Scope streaming operations instead of RDD operations
Fix break caused by merging #6225 and #6194.
Author: Michael Armbrust <michael@databricks.com>
Closes#6244 from marmbrus/fixOrcBuildBreak and squashes the following commits:
b10e47b [Michael Armbrust] [HOTFIX] Fix ORC Build break
This PR revert #5404, change to pass the version of python in driver into JVM, check it in worker before deserializing closure, then it can works with different major version of Python.
Author: Davies Liu <davies@databricks.com>
Closes#6203 from davies/py_version and squashes the following commits:
b8fb76e [Davies Liu] fix test
6ce5096 [Davies Liu] use string for version
47c6278 [Davies Liu] check python version of worker with driver
This PR introduces several performance optimizations to `HadoopFsRelation` and `ParquetRelation2`:
1. Moving `FileStatus` listing from `DataSourceStrategy` into a cache within `HadoopFsRelation`.
This new cache generalizes and replaces the one used in `ParquetRelation2`.
This also introduces an interface change: to reuse cached `FileStatus` objects, `HadoopFsRelation.buildScan` methods now receive `Array[FileStatus]` instead of `Array[String]`.
1. When Parquet task side metadata reading is enabled, skip reading row group information when reading Parquet footers.
This is basically what PR #5334 does. Also, now we uses `ParquetFileReader.readAllFootersInParallel` to read footers in parallel.
Another optimization in question is, instead of asking `HadoopFsRelation.buildScan` to return an `RDD[Row]` for a single selected partition and then union them all, we ask it to return an `RDD[Row]` for all selected partitions. This optimization is based on the fact that Hadoop configuration broadcasting used in `NewHadoopRDD` takes 34% time in the following microbenchmark. However, this complicates data source user code because user code must merge partition values manually.
To check the cost of broadcasting in `NewHadoopRDD`, I also did microbenchmark after removing the `broadcast` call in `NewHadoopRDD`. All results are shown below.
### Microbenchmark
#### Preparation code
Generating a partitioned table with 50k partitions, 1k rows per partition:
```scala
import sqlContext._
import sqlContext.implicits._
for (n <- 0 until 500) {
val data = for {
p <- (n * 10) until ((n + 1) * 10)
i <- 0 until 1000
} yield (i, f"val_$i%04d", f"$p%04d")
data.
toDF("a", "b", "p").
write.
partitionBy("p").
mode("append").
parquet(path)
}
```
#### Benchmarking code
```scala
import sqlContext._
import sqlContext.implicits._
import org.apache.spark.sql.types._
import com.google.common.base.Stopwatch
val path = "hdfs://localhost:9000/user/lian/5k"
def benchmark(n: Int)(f: => Unit) {
val stopwatch = new Stopwatch()
def run() = {
stopwatch.reset()
stopwatch.start()
f
stopwatch.stop()
stopwatch.elapsedMillis()
}
val records = (0 until n).map(_ => run())
(0 until n).foreach(i => println(s"Round $i: ${records(i)} ms"))
println(s"Average: ${records.sum / n.toDouble} ms")
}
benchmark(3) { read.parquet(path).explain(extended = true) }
```
#### Results
Before:
```
Round 0: 72528 ms
Round 1: 68938 ms
Round 2: 65372 ms
Average: 68946.0 ms
```
After:
```
Round 0: 59499 ms
Round 1: 53645 ms
Round 2: 53844 ms
Round 3: 49093 ms
Round 4: 50555 ms
Average: 53327.2 ms
```
Also removing Hadoop configuration broadcasting:
(Note that I was testing on a local laptop, thus network cost is pretty low.)
```
Round 0: 15806 ms
Round 1: 14394 ms
Round 2: 14699 ms
Round 3: 15334 ms
Round 4: 14123 ms
Average: 14871.2 ms
```
Author: Cheng Lian <lian@databricks.com>
Closes#6225 from liancheng/spark-7673 and squashes the following commits:
2d58a2b [Cheng Lian] Skips reading row group information when using task side metadata reading
7aa3748 [Cheng Lian] Optimizes FileStatusCache by introducing a map from parent directories to child files
ba41250 [Cheng Lian] Reuses HadoopFsRelation FileStatusCache in ParquetRelation2
3d278f7 [Cheng Lian] Fixes a bug when reading a single Parquet data file
b84612a [Cheng Lian] Fixes Scala style issue
6a08b02 [Cheng Lian] WIP: Moves file status cache into HadoopFSRelation
cc liancheng marmbrus
Author: Yin Huai <yhuai@databricks.com>
Closes#6130 from yhuai/directOutput and squashes the following commits:
312b07d [Yin Huai] A data source can use spark.sql.sources.outputCommitterClass to override the output committer.
A modified version of https://github.com/apache/spark/pull/6110, use `semanticEquals` to make it more efficient.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6173 from cloud-fan/7269 and squashes the following commits:
e4a3cc7 [Wenchen Fan] address comments
cc02045 [Wenchen Fan] consider elements length equal
d7ff8f4 [Wenchen Fan] fix 7269
spark-sql>
> explain extended
> select * from (
> select key from src union all
> select key from src) t;
now the spark plan will print children in argString
```
== Physical Plan ==
Union[ HiveTableScan key#1, (MetastoreRelation default, src, None), None,
HiveTableScan key#3, (MetastoreRelation default, src, None), None]
HiveTableScan key#1, (MetastoreRelation default, src, None), None
HiveTableScan key#3, (MetastoreRelation default, src, None), None
```
after this patch:
```
== Physical Plan ==
Union
HiveTableScan [key#1], (MetastoreRelation default, src, None), None
HiveTableScan [key#3], (MetastoreRelation default, src, None), None
```
I have tested this locally
Author: scwf <wangfei1@huawei.com>
Closes#6144 from scwf/fix-argString and squashes the following commits:
1a642e0 [scwf] fix treenode argString
This PR updates PR #6135 authored by zhzhan from Hortonworks.
----
This PR implements a Spark SQL data source for accessing ORC files.
> **NOTE**
>
> Although ORC is now an Apache TLP, the codebase is still tightly coupled with Hive. That's why the new ORC data source is under `org.apache.spark.sql.hive` package, and must be used with `HiveContext`. However, it doesn't require existing Hive installation to access ORC files.
1. Saving/loading ORC files without contacting Hive metastore
1. Support for complex data types (i.e. array, map, and struct)
1. Aware of common optimizations provided by Spark SQL:
- Column pruning
- Partitioning pruning
- Filter push-down
1. Schema evolution support
1. Hive metastore table conversion
This PR also include initial work done by scwf from Huawei (PR #3753).
Author: Zhan Zhang <zhazhan@gmail.com>
Author: Cheng Lian <lian@databricks.com>
Closes#6194 from liancheng/polishing-orc and squashes the following commits:
55ecd96 [Cheng Lian] Reorganizes ORC test suites
d4afeed [Cheng Lian] Addresses comments
21ada22 [Cheng Lian] Adds @since and @Experimental annotations
128bd3b [Cheng Lian] ORC filter bug fix
d734496 [Cheng Lian] Polishes the ORC data source
2650a42 [Zhan Zhang] resolve review comments
3c9038e [Zhan Zhang] resolve review comments
7b3c7c5 [Zhan Zhang] save mode fix
f95abfd [Zhan Zhang] reuse test suite
7cc2c64 [Zhan Zhang] predicate fix
4e61c16 [Zhan Zhang] minor change
305418c [Zhan Zhang] orc data source support
This PR makes pipeline stages in Python copyable and hence simplifies some implementations. It also includes the following changes:
1. Rename `paramMap` and `defaultParamMap` to `_paramMap` and `_defaultParamMap`, respectively.
2. Accept a list of param maps in `fit`.
3. Use parent uid and name to identify param.
jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#6088 from mengxr/SPARK-7380 and squashes the following commits:
413c463 [Xiangrui Meng] remove unnecessary doc
4159f35 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7380
611c719 [Xiangrui Meng] fix python style
68862b8 [Xiangrui Meng] update _java_obj initialization
927ad19 [Xiangrui Meng] fix ml/tests.py
0138fc3 [Xiangrui Meng] update feature transformers and fix a bug in RegexTokenizer
9ca44fb [Xiangrui Meng] simplify Java wrappers and add tests
c7d84ef [Xiangrui Meng] update ml/tests.py to test copy params
7e0d27f [Xiangrui Meng] merge master
46840fb [Xiangrui Meng] update wrappers
b6db1ed [Xiangrui Meng] update all self.paramMap to self._paramMap
46cb6ed [Xiangrui Meng] merge master
a163413 [Xiangrui Meng] fix style
1042e80 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7380
9630eae [Xiangrui Meng] fix Identifiable._randomUID
13bd70a [Xiangrui Meng] update ml/tests.py
64a536c [Xiangrui Meng] use _fit/_transform/_evaluate to simplify the impl
02abf13 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into copyable-python
66ce18c [Joseph K. Bradley] some cleanups before sending to Xiangrui
7431272 [Joseph K. Bradley] Rebased with master
<!-- Reviewable:start -->
[<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/6091)
<!-- Reviewable:end -->
Author: Cheng Lian <lian@databricks.com>
Closes#6091 from liancheng/spark-7570 and squashes the following commits:
8ff07e8 [Cheng Lian] Ignores _temporary during partition discovery
Replace the DriverQuirks with JdbcDialect(s) (and MySQLDialect/PostgresDialect)
and allow developers to change the dialects on the fly (for new JDBCRRDs only).
Some types (like an unsigned 64bit number) can be trivially mapped to java.
The status quo is that the RRD will fail to load.
This patch makes it possible to overwrite the type mapping to read e.g.
64Bit numbers as strings and handle them afterwards in software.
JDBCSuite has an example that maps all types to String, which should always
work (at the cost of extra code afterwards).
As a side effect it should now be possible to develop simple dialects
out-of-tree and even with spark-shell.
Author: Rene Treffer <treffer@measite.de>
Closes#5555 from rtreffer/jdbc-dialects and squashes the following commits:
3cbafd7 [Rene Treffer] [SPARK-6888] ignore classes belonging to changed API in MIMA report
fe7e2e8 [Rene Treffer] [SPARK-6888] Make the jdbc driver handling user-definable
This patch fixes two things:
**SPARK-7627.** Cached RDDs no longer light up on the job page. This is a simple fix.
**SPARK-7472.** Display skipped stages differently from normal stages.
The latter is a major UX issue. Because we link the job viz to the stage viz even for skipped stages, the user may inadvertently click into the stage page of a skipped stage, which is empty.
-------------------
<img src="https://cloud.githubusercontent.com/assets/2133137/7675241/de1a3da6-fcea-11e4-8101-88055cef78c5.png" width="300px" />
Author: Andrew Or <andrew@databricks.com>
Closes#6171 from andrewor14/dag-viz-skipped and squashes the following commits:
f261797 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-skipped
0eda358 [Andrew Or] Tweak skipped stage border color
c604150 [Andrew Or] Tweak grayscale colors
7010676 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-skipped
762b541 [Andrew Or] Use special prefix for stage clusters to avoid collisions
51c95b9 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-skipped
b928cd4 [Andrew Or] Fix potential leak + write tests for it
7c4c364 [Andrew Or] Show skipped stages differently
7cc34ce [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-skipped
c121fa2 [Andrew Or] Fix cache color
Fixed the following warnings in `make clean html` under `python/docs`:
~~~
/Users/meng/src/spark/python/pyspark/mllib/evaluation.py:docstring of pyspark.mllib.evaluation.RankingMetrics.ndcgAt:3: ERROR: Unexpected indentation.
/Users/meng/src/spark/python/pyspark/mllib/evaluation.py:docstring of pyspark.mllib.evaluation.RankingMetrics.ndcgAt:4: WARNING: Block quote ends without a blank line; unexpected unindent.
/Users/meng/src/spark/python/pyspark/mllib/fpm.py:docstring of pyspark.mllib.fpm.FPGrowth.train:3: ERROR: Unexpected indentation.
/Users/meng/src/spark/python/pyspark/mllib/fpm.py:docstring of pyspark.mllib.fpm.FPGrowth.train:4: WARNING: Block quote ends without a blank line; unexpected unindent.
/Users/meng/src/spark/python/pyspark/sql/__init__.py:docstring of pyspark.sql.DataFrame.replace:16: WARNING: Field list ends without a blank line; unexpected unindent.
/Users/meng/src/spark/python/pyspark/streaming/kafka.py:docstring of pyspark.streaming.kafka.KafkaUtils.createRDD:8: ERROR: Unexpected indentation.
/Users/meng/src/spark/python/pyspark/streaming/kafka.py:docstring of pyspark.streaming.kafka.KafkaUtils.createRDD:9: WARNING: Block quote ends without a blank line; unexpected unindent.
~~~
davies
Author: Xiangrui Meng <meng@databricks.com>
Closes#6221 from mengxr/SPARK-6657 and squashes the following commits:
e3f83fe [Xiangrui Meng] fix sql and streaming doc warnings
2b4371e [Xiangrui Meng] fix mllib python doc warnings
JIRA: https://issues.apache.org/jira/browse/SPARK-7299
When connecting with oracle db through jdbc, the precision and scale of `BigDecimal` object returned by `ResultSet.getBigDecimal` is not correctly matched to the table schema reported by `ResultSetMetaData.getPrecision` and `ResultSetMetaData.getScale`.
So in case you insert a value like `19999` into a column with `NUMBER(12, 2)` type, you get through a `BigDecimal` object with scale as 0. But the dataframe schema has correct type as `DecimalType(12, 2)`. Thus, after you save the dataframe into parquet file and then retrieve it, you will get wrong result `199.99`.
Because it is reported to be problematic on jdbc connection with oracle db. It might be difficult to add test case for it. But according to the user's test on JIRA, it solves this problem.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5833 from viirya/jdbc_decimal_precision and squashes the following commits:
69bc2b5 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into jdbc_decimal_precision
928f864 [Liang-Chi Hsieh] Add comments.
5f9da94 [Liang-Chi Hsieh] Set up Decimal's precision and scale according to table schema instead of returned BigDecimal.
The `toString` method of `LogisticRegressionModel` calls `get` method on an Option (threshold) without a safeguard. In spark-shell, the following code `val model = algorithm.run(data).clearThreshold()` in lbfgs code will fail as `toString `method will be called right after `clearThreshold()` to show the results in the REPL.
Author: Shuo Xiang <shuoxiangpub@gmail.com>
Closes#6224 from coderxiang/getorelse and squashes the following commits:
d5f53c9 [Shuo Xiang] use getOrElse for getting the threshold of LR model
5f109b4 [Shuo Xiang] Merge remote-tracking branch 'upstream/master'
c5c5bfe [Shuo Xiang] Merge remote-tracking branch 'upstream/master'
98804c9 [Shuo Xiang] fix bug in topBykey and update test
Learnt a lesson from SPARK-7655: Spark should avoid to use `scala.concurrent.ExecutionContext.Implicits.global` because the user may submit blocking actions to `scala.concurrent.ExecutionContext.Implicits.global` and exhaust all threads in it. This could crash Spark. So Spark should always use its own thread pools for safety.
This PR removes all usages of `scala.concurrent.ExecutionContext.Implicits.global` and uses proper thread pools to replace them.
Author: zsxwing <zsxwing@gmail.com>
Closes#6223 from zsxwing/SPARK-7693 and squashes the following commits:
a33ff06 [zsxwing] Decrease the max thread number from 1024 to 128
cf4b3fc [zsxwing] Remove "import scala.concurrent.ExecutionContext.Implicits.global"
It's a follow-up of https://github.com/apache/spark/pull/5154, we can speed up scala udf evaluation by create type converter in advance.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6182 from cloud-fan/tmp and squashes the following commits:
241cfe9 [Wenchen Fan] use converter in ScalaUdf
SPARK-6514 - Use correct region
SPARK-5960 - Allow AWS Credentials to be directly passed
SPARK-6656 - Specify kinesis application name explicitly
SPARK-7679 - Upgrade to latest KCL and AWS SDK.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#6147 from tdas/kinesis-api-update and squashes the following commits:
f23ea77 [Tathagata Das] Updated versions and updated APIs
373b201 [Tathagata Das] Updated Kinesis API
Author: Michael Armbrust <michael@databricks.com>
Closes#6167 from marmbrus/configureIsolation and squashes the following commits:
6147cbe [Michael Armbrust] filter other conf
22cc3bc7 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into configureIsolation
07476ee [Michael Armbrust] filter empty prefixes
dfdf19c [Michael Armbrust] [SPARK-6906][SQL] Allow configuration of classloader isolation for hive
