Minor cleanups discussed with [~mengxr]:
* move OneVsRest from reduction to classification sub-package
* make model constructor private
Some doc cleanups too
CC: harsha2010 Could you please verify this looks OK? Thanks!
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#6097 from jkbradley/onevsrest-cleanup and squashes the following commits:
4ecd48d [Joseph K. Bradley] org imports
430b065 [Joseph K. Bradley] moved OneVsRest from reduction subpackage to classification. small java doc style fixes
9f8b9b9 [Joseph K. Bradley] Small cleanups to OneVsRest. Made model constructor private to ml package.
(cherry picked from commit 96c4846db8)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
Added feature transformer subsection to spark.ml guide, with HashingTF and Tokenizer. Added JavaHashingTFSuite to test Java examples in new guide.
I've run Scala, Python examples in the Spark/PySpark shells. I ran the Java examples via the test suite (with small modifications for printing).
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#6093 from jkbradley/hashingtf-guide and squashes the following commits:
d5d213f [Joseph K. Bradley] small fix
dd6e91a [Joseph K. Bradley] fixes from code review of user guide
33c3ff9 [Joseph K. Bradley] small fix
bc6058c [Joseph K. Bradley] fix link
361a174 [Joseph K. Bradley] Added subsection for feature transformers to spark.ml guide, with HashingTF and Tokenizer. Added JavaHashingTFSuite to test Java examples in new guide
(cherry picked from commit f0c1bc3472)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
jira: https://issues.apache.org/jira/browse/SPARK-7496
Update LDA subsection of clustering section of MLlib programming guide to include OnlineLDA.
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#6046 from hhbyyh/ldaDocument and squashes the following commits:
4b6fbfa [Yuhao Yang] add online paper and some comparison
fd4c983 [Yuhao Yang] update lda document for optimizers
(cherry picked from commit 1d703660d4)
Signed-off-by: Joseph K. Bradley <joseph@databricks.com>
`scala.Math` is deprecated since 2.8. This PR only touchs `Math` usages in MLlib. dbtsai
Author: Xiangrui Meng <meng@databricks.com>
Closes#6092 from mengxr/SPARK-7571 and squashes the following commits:
fe8f8d3 [Xiangrui Meng] Math -> math
(cherry picked from commit a4874b0d18)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
Few jdbc drivers like SybaseIQ support passing username and password only through connection properties. So the same needs to be supported for
SQLContext.jdbc, dataframe.createJDBCTable and dataframe.insertIntoJDBC.
Added as default arguments or overrided function to support backward compatability.
Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com>
Closes#6009 from gvramana/add_jdbc_conn_properties and squashes the following commits:
396a0d0 [Venkata Ramana Gollamudi] fixed comments
d66dd8c [Venkata Ramana Gollamudi] fixed comments
1b8cd8c [Venkata Ramana Gollamudi] Support jdbc connection properties
(cherry picked from commit 455551d1c6)
Signed-off-by: Reynold Xin <rxin@databricks.com>
We make special treatment for +inf in `Bucketizer`. This could be simplified by always including the largest split value in the last bucket. E.g., (x1, x2, x3) defines buckets [x1, x2) and [x2, x3]. This shouldn't affect user code much, and there are applications that need to include the right-most value. For example, we can bucketize ratings from 0 to 10 to bad, neutral, and good with splits 0, 4, 6, 10. It may reads weird if the users need to put 0, 4, 6, 10.1 (or 11).
This also update the impl to use `Arrays.binarySearch` and `withClue` in test.
yinxusen jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes#6075 from mengxr/SPARK-7559 and squashes the following commits:
e28f910 [Xiangrui Meng] update bucketizer impl
(cherry picked from commit 23b9863e2a)
Signed-off-by: Joseph K. Bradley <joseph@databricks.com>
…roblem
Pick up newer version of dependency with fix for SPARK-2018. The update involved patching the ning/compress LZF library to handle big endian systems correctly.
Credit goes to gireeshpunathil for diagnosing the problem, and cowtowncoder for fixing it.
Spark tests run clean for me.
Author: Tim Ellison <t.p.ellison@gmail.com>
Closes#6077 from tellison/UpgradeLZF and squashes the following commits:
ad8d4ef [Tim Ellison] [SPARK-2018] [CORE] Upgrade LZF library to fix endian serialization problem
(cherry picked from commit 5438f49ccf)
Signed-off-by: Sean Owen <sowen@cloudera.com>
Added LinearRegression Python API
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#6016 from brkyvz/ml-reg and squashes the following commits:
11c9ef9 [Burak Yavuz] address comments
1027a40 [Burak Yavuz] fix typo
4c699ad [Burak Yavuz] added tree regressor api
8afead2 [Burak Yavuz] made mixin for DT
fa51c74 [Burak Yavuz] save additions
0640d48 [Burak Yavuz] added ml.regression
82aac48 [Burak Yavuz] added linear regression
(cherry picked from commit 8e935b0a21)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#5831 from cloud-fan/7276 and squashes the following commits:
ee4a1e1 [Wenchen Fan] fix rebase mistake
a3b565d [Wenchen Fan] refactor
99deb5d [Wenchen Fan] add test
f1f67ad [Wenchen Fan] fix 7276
(cherry picked from commit 4e290522c2)
Signed-off-by: Michael Armbrust <michael@databricks.com>
This fixes the label bleeding issue described in the JIRA and pictured in the screenshots below. I also took the opportunity to move some code to the places that they belong more to. In particular:
(1) Drawing cluster labels is now implemented in my branch of dagre-d3 instead of in Spark
(2) All graph styling is now moved from Scala to JS
Note that these changes are related because our existing mechanism of "tacking on cluster labels" afterwards isn't flexible enough for us to fix issues like this one easily. For the other half of the changes, visit http://github.com/andrewor14/dagre-d3.
-------------------
**Before.**
<img src="https://cloud.githubusercontent.com/assets/2133137/7582769/b1423440-f845-11e4-8248-b3446a01bf79.png" width="300px"/>
-------------------
**After.**
<img src="https://cloud.githubusercontent.com/assets/2133137/7582742/74891ae6-f845-11e4-96c4-41c7b8aedbdf.png" width="400px"/>
Author: Andrew Or <andrew@databricks.com>
Closes#6076 from andrewor14/dag-viz-bleed and squashes the following commits:
5858d7a [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-bleed
c686dc4 [Andrew Or] Fix tooltip placement
d908c36 [Andrew Or] Add link to dagre-d3 changes (minor)
4a4fb58 [Andrew Or] Fix bleeding + move all styling to JS
(cherry picked from commit 65697bbeaf)
Signed-off-by: Andrew Or <andrew@databricks.com>
Minor improvement, now we can use `Column` as extraction expression.
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6080 from cloud-fan/tmp and squashes the following commits:
0fdefb7 [Wenchen Fan] support column in field accessor
(cherry picked from commit bfcaf8adcd)
Signed-off-by: Reynold Xin <rxin@databricks.com>
This PR adds partitioning support for the external data sources API. It aims to simplify development of file system based data sources, and provide first class partitioning support for both read path and write path. Existing data sources like JSON and Parquet can be simplified with this work.
## New features provided
1. Hive compatible partition discovery
This actually generalizes the partition discovery strategy used in Parquet data source in Spark 1.3.0.
1. Generalized partition pruning optimization
Now partition pruning is handled during physical planning phase. Specific data sources don't need to worry about this harness anymore.
(This also implies that we can remove `CatalystScan` after migrating the Parquet data source, since now we don't need to pass Catalyst expressions to data source implementations.)
1. Insertion with dynamic partitions
When inserting data to a `FSBasedRelation`, data can be partitioned dynamically by specified partition columns.
## New structures provided
### Developer API
1. `FSBasedRelation`
Base abstract class for file system based data sources.
1. `OutputWriter`
Base abstract class for output row writers, responsible for writing a single row object.
1. `FSBasedRelationProvider`
A new relation provider for `FSBasedRelation` subclasses. Note that data sources extending `FSBasedRelation` don't need to extend `RelationProvider` and `SchemaRelationProvider`.
### User API
New overloaded versions of
1. `DataFrame.save()`
1. `DataFrame.saveAsTable()`
1. `SQLContext.load()`
are provided to allow users to save/load DataFrames with user defined dynamic partition columns.
### Spark SQL query planning
1. `InsertIntoFSBasedRelation`
Used to implement write path for `FSBasedRelation`s.
1. New rules for `FSBasedRelation` in `DataSourceStrategy`
These are added to hook `FSBasedRelation` into physical query plan in read path, and perform partition pruning.
## TODO
- [ ] Use scratch directories when overwriting a table with data selected from itself.
Currently, this is not supported, because the table been overwritten is always deleted before writing any data to it.
- [ ] When inserting with dynamic partition columns, use external sorter to group the data first.
This ensures that we only need to open a single `OutputWriter` at a time. For data sources like Parquet, `OutputWriter`s can be quite memory consuming. One issue is that, this approach breaks the row distribution in the original DataFrame. However, we did't promise to preserve data distribution when writing a DataFrame.
- [x] More tests. Specifically, test cases for
- [x] Self-join
- [x] Loading partitioned relations with a subset of partition columns stored in data files.
- [x] `SQLContext.load()` with user defined dynamic partition columns.
## Parquet data source migration
Parquet data source migration is covered in PR https://github.com/liancheng/spark/pull/6, which is against this PR branch and for preview only. A formal PR need to be made after this one is merged.
Author: Cheng Lian <lian@databricks.com>
Closes#5526 from liancheng/partitioning-support and squashes the following commits:
5351a1b [Cheng Lian] Fixes compilation error introduced while rebasing
1f9b1a5 [Cheng Lian] Tweaks data schema passed to FSBasedRelations
43ba50e [Cheng Lian] Avoids serializing generated projection code
edf49e7 [Cheng Lian] Removed commented stale code block
348a922 [Cheng Lian] Adds projection in FSBasedRelation.buildScan(requiredColumns, inputPaths)
ad4d4de [Cheng Lian] Enables HDFS style globbing
8d12e69 [Cheng Lian] Fixes compilation error
c71ac6c [Cheng Lian] Addresses comments from @marmbrus
7552168 [Cheng Lian] Fixes typo in MimaExclude.scala
0349e09 [Cheng Lian] Fixes compilation error introduced while rebasing
52b0c9b [Cheng Lian] Adjusts project/MimaExclude.scala
c466de6 [Cheng Lian] Addresses comments
bc3f9b4 [Cheng Lian] Uses projection to separate partition columns and data columns while inserting rows
795920a [Cheng Lian] Fixes compilation error after rebasing
0b8cd70 [Cheng Lian] Adds Scala/Catalyst row conversion when writing non-partitioned tables
fa543f3 [Cheng Lian] Addresses comments
5849dd0 [Cheng Lian] Fixes doc typos. Fixes partition discovery refresh.
51be443 [Cheng Lian] Replaces FSBasedRelation.outputCommitterClass with FSBasedRelation.prepareForWrite
c4ed4fe [Cheng Lian] Bug fixes and a new test suite
a29e663 [Cheng Lian] Bug fix: should only pass actuall data files to FSBaseRelation.buildScan
5f423d3 [Cheng Lian] Bug fixes. Lets data source to customize OutputCommitter rather than OutputFormat
54c3d7b [Cheng Lian] Enforces that FileOutputFormat must be used
be0c268 [Cheng Lian] Uses TaskAttempContext rather than Configuration in OutputWriter.init
0bc6ad1 [Cheng Lian] Resorts to new Hadoop API, and now FSBasedRelation can customize output format class
f320766 [Cheng Lian] Adds prepareForWrite() hook, refactored writer containers
422ff4a [Cheng Lian] Fixes style issue
ce52353 [Cheng Lian] Adds new SQLContext.load() overload with user defined dynamic partition columns
8d2ff71 [Cheng Lian] Merges partition columns when reading partitioned relations
ca1805b [Cheng Lian] Removes duplicated partition discovery code in new Parquet
f18dec2 [Cheng Lian] More strict schema checking
b746ab5 [Cheng Lian] More tests
9b487bf [Cheng Lian] Fixes compilation errors introduced while rebasing
ea6c8dd [Cheng Lian] Removes remote debugging stuff
327bb1d [Cheng Lian] Implements partitioning support for data sources API
3c5073a [Cheng Lian] Fixes SaveModes used in test cases
fb5a607 [Cheng Lian] Fixes compilation error
9d17607 [Cheng Lian] Adds the contract that OutputWriter should have zero-arg constructor
5de194a [Cheng Lian] Forgot Apache licence header
95d0b4d [Cheng Lian] Renames PartitionedSchemaRelationProvider to FSBasedRelationProvider
770b5ba [Cheng Lian] Adds tests for FSBasedRelation
3ba9bbf [Cheng Lian] Adds DataFrame.saveAsTable() overrides which support partitioning
1b8231f [Cheng Lian] Renames FSBasedPrunedFilteredScan to FSBasedRelation
aa8ba9a [Cheng Lian] Javadoc fix
012ed2d [Cheng Lian] Adds PartitioningOptions
7dd8dd5 [Cheng Lian] Adds new interfaces and stub methods for data sources API partitioning support
(cherry picked from commit 0595b6de8f)
Signed-off-by: Cheng Lian <lian@databricks.com>
Author: Wenchen Fan <cloud0fan@outlook.com>
Closes#6079 from cloud-fan/unapply and squashes the following commits:
40da442 [Wenchen Fan] one more
7d90a05 [Wenchen Fan] cleanup unapply in DataTypes
(cherry picked from commit 831504cf6b)
Signed-off-by: Reynold Xin <rxin@databricks.com>
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#6003 from adrian-wang/pynareplace and squashes the following commits:
672efba [Daoyuan Wang] remove py2.7 feature
4a148f7 [Daoyuan Wang] to_replace support dict, value support single value, and add full tests
9e232e7 [Daoyuan Wang] rename scala map
af0268a [Daoyuan Wang] remove na
63ac579 [Daoyuan Wang] add na.replace in pyspark
(cherry picked from commit d86ce84584)
Signed-off-by: Reynold Xin <rxin@databricks.com>
Such that a checkpoint RDD does not go into random scopes on the UI, e.g. `take`. We've seen this in streaming.
Author: Andrew Or <andrew@databricks.com>
Closes#6004 from andrewor14/dag-viz-checkpoint and squashes the following commits:
9217439 [Andrew Or] Fix checkpoints
4ae8806 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-checkpoint
19bc07b [Andrew Or] Treat checkpoint as an RDD operation
(cherry picked from commit f3e8e60063)
Signed-off-by: Andrew Or <andrew@databricks.com>
The sbt part of the build is hacky; it basically tricks sbt
into generating the zip by using a generator, but returns
an empty list for the generated files so that nothing is
actually added to the assembly.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#6022 from vanzin/SPARK-7485 and squashes the following commits:
22c1e04 [Marcelo Vanzin] Remove unneeded code.
4893622 [Marcelo Vanzin] [SPARK-7485] [build] Remove pyspark files from assembly.
(cherry picked from commit 82e890fb19)
Signed-off-by: Andrew Or <andrew@databricks.com>
As PR #5580 we have created pyspark.zip on building and set PYTHONPATH to python/lib/pyspark.zip, so to keep consistence update this.
Author: linweizhong <linweizhong@huawei.com>
Closes#6047 from Sephiroth-Lin/pyspark_pythonpath and squashes the following commits:
8cc3d96 [linweizhong] Set PYTHONPATH to python/lib/pyspark.zip rather than python/pyspark as PR#5580 we have create pyspark.zip on build
(cherry picked from commit 9847875266)
Signed-off-by: Andrew Or <andrew@databricks.com>
add docs for https://issues.apache.org/jira/browse/SPARK-6994
Author: vidmantas zemleris <vidmantas@vinted.com>
Closes#6030 from vidma/docs/row-with-named-fields and squashes the following commits:
241b401 [vidmantas zemleris] [SPARK-6994][SQL] Update docs for fetching Row fields by name
(cherry picked from commit 640f63b959)
Signed-off-by: Reynold Xin <rxin@databricks.com>
Author: Reynold Xin <rxin@databricks.com>
Closes#6068 from rxin/drop-column and squashes the following commits:
9d7d5ec [Reynold Xin] [SPARK-7509][SQL] DataFrame.drop in Python for dropping columns.
(cherry picked from commit 028ad4bd29)
Signed-off-by: Reynold Xin <rxin@databricks.com>
This is a follow up of #5876 and should be merged after #5876.
Let's wait for unit testing result from Jenkins.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#5963 from chenghao-intel/useIsolatedClient and squashes the following commits:
f87ace6 [Cheng Hao] remove the TODO and add `resolved condition` for HiveTable
a8260e8 [Cheng Hao] Update code as feedback
f4e243f [Cheng Hao] remove the serde setting for SequenceFile
d166afa [Cheng Hao] style issue
d25a4aa [Cheng Hao] Add SerDe support for CTAS
(cherry picked from commit e35d878be3)
Signed-off-by: Michael Armbrust <michael@databricks.com>
This should also close https://github.com/apache/spark/pull/5870
Author: Reynold Xin <rxin@databricks.com>
Closes#6066 from rxin/dropDups and squashes the following commits:
130692f [Reynold Xin] [SPARK-7324][SQL] DataFrame.dropDuplicates
(cherry picked from commit b6bf4f76c7)
Signed-off-by: Michael Armbrust <michael@databricks.com>
JIRA issue [here](https://issues.apache.org/jira/browse/SPARK-5893).
One thing to make clear, the `buckets` parameter, which is an array of `Double`, performs as split points. Say,
```scala
buckets = Array(-0.5, 0.0, 0.5)
```
splits the real number into 4 ranges, (-inf, -0.5], (-0.5, 0.0], (0.0, 0.5], (0.5, +inf), which is encoded as 0, 1, 2, 3.
Author: Xusen Yin <yinxusen@gmail.com>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5980 from yinxusen/SPARK-5893 and squashes the following commits:
dc8c843 [Xusen Yin] Merge pull request #4 from jkbradley/yinxusen-SPARK-5893
1ca973a [Joseph K. Bradley] one more bucketizer test
34f124a [Joseph K. Bradley] Removed lowerInclusive, upperInclusive params from Bucketizer, and used splits instead.
eacfcfa [Xusen Yin] change ML attribute from splits into buckets
c3cc770 [Xusen Yin] add more unit test for binary search
3a16cc2 [Xusen Yin] refine comments and names
ac77859 [Xusen Yin] fix style error
fb30d79 [Xusen Yin] fix and test binary search
2466322 [Xusen Yin] refactor Bucketizer
11fb00a [Xusen Yin] change it into an Estimator
998bc87 [Xusen Yin] check buckets
4024cf1 [Xusen Yin] add test suite
5fe190e [Xusen Yin] add bucketizer
(cherry picked from commit 35fb42a0b0)
Signed-off-by: Joseph K. Bradley <joseph@databricks.com>
So users that are interested in this can track it easily.
Author: Reynold Xin <rxin@databricks.com>
Closes#6067 from rxin/SPARK-7550 and squashes the following commits:
ee0e34c [Reynold Xin] Updated DataFrame.saveAsTable Hive warning to include SPARK-7550 ticket.
(cherry picked from commit 87229c95c6)
Signed-off-by: Reynold Xin <rxin@databricks.com>
Author: Reynold Xin <rxin@databricks.com>
Closes#6062 from rxin/agg-retain-doc and squashes the following commits:
43e511e [Reynold Xin] [SPARK-7462][SQL] Update documentation for retaining grouping columns in DataFrames.
(cherry picked from commit 3a9b6997df)
Signed-off-by: Reynold Xin <rxin@databricks.com>
Author: madhukar <phatak.dev@gmail.com>
Closes#5654 from phatak-dev/master and squashes the following commits:
386f407 [madhukar] #5654 updated for all the methods
2c997c5 [madhukar] Merge branch 'master' of https://github.com/apache/spark
00bc819 [madhukar] Merge branch 'master' of https://github.com/apache/spark
2a802c6 [madhukar] #5654 updated the doc according to comments
866e8df [madhukar] [SPARK-7084] improve saveAsTable documentation
(cherry picked from commit 57255dcd79)
Signed-off-by: Reynold Xin <rxin@databricks.com>
As a follow-up to https://github.com/apache/spark/pull/5944
Author: Reynold Xin <rxin@databricks.com>
Closes#6064 from rxin/jointype-better-error and squashes the following commits:
7629bf7 [Reynold Xin] [SQL] Show better error messages for incorrect join types in DataFrames.
(cherry picked from commit 4f4dbb030c)
Signed-off-by: Reynold Xin <rxin@databricks.com>
Currently there's no chance to close the file correctly after the iteration is finished, change to `CompletionIterator` to avoid resource leakage.
Author: jerryshao <saisai.shao@intel.com>
Closes#6050 from jerryshao/close-file-correctly and squashes the following commits:
52dfaf5 [jerryshao] Close files correctly when iterator is finished
(cherry picked from commit 25c01c5484)
Signed-off-by: Tathagata Das <tathagata.das1565@gmail.com>
JIRA: https://issues.apache.org/jira/browse/SPARK-7516
In sql-programming-guide, deprecated python data frame api inferSchema() should be replaced by createDataFrame():
schemaPeople = sqlContext.inferSchema(people) ->
schemaPeople = sqlContext.createDataFrame(people)
Author: gchen <chenguancheng@gmail.com>
Closes#6041 from gchen/python-docs and squashes the following commits:
c27eb7c [gchen] replace inferSchema() with createDataFrame()
(cherry picked from commit 8e674331d9)
Signed-off-by: Reynold Xin <rxin@databricks.com>
Patch for SPARK-7508
This logs warn then generates a response which include the message body and stack trace as text/plain, no-cache. The exit code is 500.
In practise (in some tests in SPARK-1537 to be precise), jetty is getting in between this servlet and the web response the user sees —the body of the response is lost for any error response (500, even 404 and bad request). The standard Jetty handlers must be getting in the way.
This patch doesn't address that, it ensures that
1. if the jetty handlers were put to one side the users would see the errors
2. at least the exceptions appear in the server-side logs.
This is better to users saying "I saw a 500 error" and you not having anything in the logs to see what went wrong.
Author: Steve Loughran <stevel@hortonworks.com>
Closes#6033 from steveloughran/stevel/feature/SPARK-7508-JettyUtils and squashes the following commits:
584836f [Steve Loughran] SPARK-7508 drop trailing semicolon
ad6f185 [Steve Loughran] SPARK-7508: jetty handles exception reporting itself; spark just sets this up and logs exceptions before being relayed
258d9f9 [Steve Loughran] SPARK-7508 fix typo manually-edited before patch pushed
69c8263 [Steve Loughran] SPARK-7508 JettyUtils-generated servlets to log & report all errors
Updated Java, Scala, Python, and R.
Author: Reynold Xin <rxin@databricks.com>
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#5996 from rxin/groupby-retain and squashes the following commits:
aac7119 [Reynold Xin] Merge branch 'groupby-retain' of github.com:rxin/spark into groupby-retain
f6858f6 [Reynold Xin] Merge branch 'master' into groupby-retain
5f923c0 [Reynold Xin] Merge pull request #15 from shivaram/sparkr-groupby-retrain
c1de670 [Shivaram Venkataraman] Revert workaround in SparkR to retain grouped cols Based on reverting code added in commit 9a6be746ef
b8b87e1 [Reynold Xin] Fixed DataFrameJoinSuite.
d910141 [Reynold Xin] Updated rest of the files
1e6e666 [Reynold Xin] [SPARK-7462] By default retain group by columns in aggregate
(cherry picked from commit 0a4844f90a)
Signed-off-by: Reynold Xin <rxin@databricks.com>
Currently attempt to start a streamingContext while another one is started throws a confusing exception that the action name JobScheduler is already registered. Instead its best to throw a proper exception as it is not supported.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#5907 from tdas/SPARK-7361 and squashes the following commits:
fb81c4a [Tathagata Das] Fix typo
a9cd5bb [Tathagata Das] Added startSite to StreamingContext
5fdfc0d [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-7361
5870e2b [Tathagata Das] Added check for multiple streaming contexts
(cherry picked from commit 1b46556999)
Signed-off-by: Tathagata Das <tathagata.das1565@gmail.com>
As is, to specify this option on command line, you have to escape the angle brackets.
Author: Bryan Cutler <bjcutler@us.ibm.com>
Closes#6049 from BryanCutler/dataFormat-option-7522 and squashes the following commits:
b34afb4 [Bryan Cutler] [SPARK-7522] Removed angle brackets from dataFormat option
(cherry picked from commit 4f8a155192)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
tdas
https://issues.apache.org/jira/browse/SPARK-7326
The problem most likely resides in DStream.slice() implementation, as shown below.
def slice(fromTime: Time, toTime: Time): Seq[RDD[T]] = {
if (!isInitialized) {
throw new SparkException(this + " has not been initialized")
}
if (!(fromTime - zeroTime).isMultipleOf(slideDuration)) {
logWarning("fromTime (" + fromTime + ") is not a multiple of slideDuration ("
+ slideDuration + ")")
}
if (!(toTime - zeroTime).isMultipleOf(slideDuration)) {
logWarning("toTime (" + fromTime + ") is not a multiple of slideDuration ("
+ slideDuration + ")")
}
val alignedToTime = toTime.floor(slideDuration, zeroTime)
val alignedFromTime = fromTime.floor(slideDuration, zeroTime)
logInfo("Slicing from " + fromTime + " to " + toTime +
" (aligned to " + alignedFromTime + " and " + alignedToTime + ")")
alignedFromTime.to(alignedToTime, slideDuration).flatMap(time => {
if (time >= zeroTime) getOrCompute(time) else None
})
}
Here after performing floor() on both fromTime and toTime, the result (alignedFromTime - zeroTime) and (alignedToTime - zeroTime) may no longer be multiple of the slidingDuration, thus making isTimeValid() check failed for all the remaining computation.
The fix is to add a new floor() function in Time.scala to respect the zeroTime while performing the floor :
def floor(that: Duration, zeroTime: Time): Time = {
val t = that.milliseconds
new Time(((this.millis - zeroTime.milliseconds) / t) * t + zeroTime.milliseconds)
}
And then change the DStream.slice to call this new floor function by passing in its zeroTime.
val alignedToTime = toTime.floor(slideDuration, zeroTime)
val alignedFromTime = fromTime.floor(slideDuration, zeroTime)
This way the alignedToTime and alignedFromTime are *really* aligned in respect to zeroTime whose value is not really a 0.
Author: Wesley Miao <wesley.miao@gmail.com>
Author: Wesley <wesley.miao@autodesk.com>
Closes#5871 from wesleymiao/spark-7326 and squashes the following commits:
82a4d8c [Wesley Miao] [SPARK-7326] [STREAMING] Performing window() on a WindowedDStream dosen't work all the time
48b4dc0 [Wesley] [SPARK-7326] [STREAMING] Performing window() on a WindowedDStream doesn't work all the time
6ade399 [Wesley] [SPARK-7326] [STREAMING] Performing window() on a WindowedDStream doesn't work all the time
2611745 [Wesley Miao] [SPARK-7326] [STREAMING] Performing window() on a WindowedDStream doesn't work all the time
(cherry picked from commit d70a076892)
Signed-off-by: Sean Owen <sowen@cloudera.com>
Bugs description:
1. There are extra commas on the top of session list.
2. The format of time in "Start at:" part is not the same as others.
3. The total number of online sessions is wrong.
Author: tianyi <tianyi.asiainfo@gmail.com>
Closes#6048 from tianyi/SPARK-7519 and squashes the following commits:
ed366b7 [tianyi] fix bug
(cherry picked from commit 2242ab31e9)
Signed-off-by: Cheng Lian <lian@databricks.com>
Modified 2 files:
python/pyspark/ml/param/_shared_params_code_gen.py
python/pyspark/ml/param/shared.py
Generated shared.py on Linux using Python 2.6.6 on Redhat Enterprise Linux Server 6.6.
python _shared_params_code_gen.py > shared.py
Only changed maxIter, regParam, rawPredictionCol based on strings from SharedParamsCodeGen.scala. Note warning was displayed when committing shared.py:
warning: LF will be replaced by CRLF in python/pyspark/ml/param/shared.py.
Author: Glenn Weidner <gweidner@us.ibm.com>
Closes#6023 from gweidner/br-7427 and squashes the following commits:
db72e32 [Glenn Weidner] [SPARK-7427] [PySpark] Make sharedParams match in Scala, Python
825e4a9 [Glenn Weidner] [SPARK-7427] [PySpark] Make sharedParams match in Scala, Python
e6a865e [Glenn Weidner] [SPARK-7427] [PySpark] Make sharedParams match in Scala, Python
1eee702 [Glenn Weidner] Merge remote-tracking branch 'upstream/master'
1ac10e5 [Glenn Weidner] Merge remote-tracking branch 'upstream/master'
cafd104 [Glenn Weidner] Merge remote-tracking branch 'upstream/master'
9bea1eb [Glenn Weidner] Merge remote-tracking branch 'upstream/master'
4a35c20 [Glenn Weidner] Merge remote-tracking branch 'upstream/master'
9790cbe [Glenn Weidner] Merge remote-tracking branch 'upstream/master'
d9c30f4 [Glenn Weidner] [SPARK-7275] [SQL] [WIP] Make LogicalRelation public
(cherry picked from commit c5aca0c27b)
Signed-off-by: Joseph K. Bradley <joseph@databricks.com>
I implement a simple PCA wrapper for easy transform of vectors by PCA for example LabeledPoint or another complicated structure.
Example of usage:
```
import org.apache.spark.mllib.regression.LinearRegressionWithSGD
import org.apache.spark.mllib.regression.LabeledPoint
import org.apache.spark.mllib.linalg.Vectors
import org.apache.spark.mllib.feature.PCA
val data = sc.textFile("data/mllib/ridge-data/lpsa.data").map { line =>
val parts = line.split(',')
LabeledPoint(parts(0).toDouble, Vectors.dense(parts(1).split(' ').map(_.toDouble)))
}.cache()
val splits = data.randomSplit(Array(0.6, 0.4), seed = 11L)
val training = splits(0).cache()
val test = splits(1)
val pca = PCA.create(training.first().features.size/2, data.map(_.features))
val training_pca = training.map(p => p.copy(features = pca.transform(p.features)))
val test_pca = test.map(p => p.copy(features = pca.transform(p.features)))
val numIterations = 100
val model = LinearRegressionWithSGD.train(training, numIterations)
val model_pca = LinearRegressionWithSGD.train(training_pca, numIterations)
val valuesAndPreds = test.map { point =>
val score = model.predict(point.features)
(score, point.label)
}
val valuesAndPreds_pca = test_pca.map { point =>
val score = model_pca.predict(point.features)
(score, point.label)
}
val MSE = valuesAndPreds.map{case(v, p) => math.pow((v - p), 2)}.mean()
val MSE_pca = valuesAndPreds_pca.map{case(v, p) => math.pow((v - p), 2)}.mean()
println("Mean Squared Error = " + MSE)
println("PCA Mean Squared Error = " + MSE_pca)
```
Author: Kirill A. Korinskiy <catap@catap.ru>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#4304 from catap/pca and squashes the following commits:
501bcd9 [Joseph K. Bradley] Small updates: removed k from Java-friendly PCA fit(). In PCASuite, converted results to set for comparison. Added an error message for bad k in PCA.
9dcc02b [Kirill A. Korinskiy] [SPARK-5521] fix scala style
1892a06 [Kirill A. Korinskiy] [SPARK-5521] PCA wrapper for easy transform vectors
(cherry picked from commit 8c07c75c98)
Signed-off-by: Joseph K. Bradley <joseph@databricks.com>
Fixes bug with PySpark cvModel not having UID
Also made small PySpark fixes: Evaluator should inherit from Params. MockModel should inherit from Model.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5968 from jkbradley/pyspark-cv-uid and squashes the following commits:
57f13cd [Joseph K. Bradley] Made CrossValidatorModel call parent init in PySpark
(cherry picked from commit 3038443e58)
Signed-off-by: Joseph K. Bradley <joseph@databricks.com>
