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* SPARK-2657 Use more compact data structures than ArrayBuffer in groupBy & ↵Matei Zaharia2014-07-251-1/+5
| | | | | | | | | | | | | | | | | | | | | | | | | | cogroup JIRA: https://issues.apache.org/jira/browse/SPARK-2657 Our current code uses ArrayBuffers for each group of values in groupBy, as well as for the key's elements in CoGroupedRDD. ArrayBuffers have a lot of overhead if there are few values in them, which is likely to happen in cases such as join. In particular, they have a pointer to an Object[] of size 16 by default, which is 24 bytes for the array header + 128 for the pointers in there, plus at least 32 for the ArrayBuffer data structure. This patch replaces the per-group buffers with a CompactBuffer class that can store up to 2 elements more efficiently (in fields of itself) and acts like an ArrayBuffer beyond that. For a key's elements in CoGroupedRDD, we use an Array of CompactBuffers instead of an ArrayBuffer of ArrayBuffers. There are some changes throughout the code to deal with CoGroupedRDD returning Array instead. We can also decide not to do that but CoGroupedRDD is a `DeveloperAPI` so I think it's okay to change it here. Author: Matei Zaharia <matei@databricks.com> Closes #1555 from mateiz/compact-groupby and squashes the following commits: 845a356 [Matei Zaharia] Lower initial size of CompactBuffer's vector to 8 07621a7 [Matei Zaharia] Review comments 0c1cd12 [Matei Zaharia] Don't use varargs in CompactBuffer.apply bdc8a39 [Matei Zaharia] Small tweak to +=, and typos f61f040 [Matei Zaharia] Fix line lengths 59da88b0 [Matei Zaharia] Fix line lengths 197cde8 [Matei Zaharia] Make CompactBuffer extend Seq to make its toSeq more efficient 775110f [Matei Zaharia] Change CoGroupedRDD to give (K, Array[Iterable[_]]) to avoid wrappers 9b4c6e8 [Matei Zaharia] Use CompactBuffer in CoGroupedRDD ed577ab [Matei Zaharia] Use CompactBuffer in groupByKey 10f0de1 [Matei Zaharia] A CompactBuffer that's more memory-efficient than ArrayBuffer for small buffers
* [SPARK-2479 (partial)][MLLIB] fix binary metrics unit testsXiangrui Meng2014-07-241-9/+27
| | | | | | | | | | | | Allow small errors in comparison. @dbtsai , this unit test blocks https://github.com/apache/spark/pull/1562 . I may need to merge this one first. We can change it to use the tools in https://github.com/apache/spark/pull/1425 after that PR gets merged. Author: Xiangrui Meng <meng@databricks.com> Closes #1576 from mengxr/fix-binary-metrics-unit-tests and squashes the following commits: 5076a7f [Xiangrui Meng] fix binary metrics unit tests
* [SPARK-2617] Correct doc and usages of preservesPartitioningXiangrui Meng2014-07-234-9/+9
| | | | | | | | | | | | | | | | | | | | | The name `preservesPartitioning` is ambiguous: 1) preserves the indices of partitions, 2) preserves the partitioner. The latter is correct and `preservesPartitioning` should really be called `preservesPartitioner` to avoid confusion. Unfortunately, this is already part of the API and we cannot change. We should be clear in the doc and fix wrong usages. This PR 1. adds notes in `maPartitions*`, 2. makes `RDD.sample` preserve partitioner, 3. changes `preservesPartitioning` to false in `RDD.zip` because the keys of the first RDD are no longer the keys of the zipped RDD, 4. fixes some wrong usages in MLlib. Author: Xiangrui Meng <meng@databricks.com> Closes #1526 from mengxr/preserve-partitioner and squashes the following commits: b361e65 [Xiangrui Meng] update doc based on pwendell's comments 3b1ba19 [Xiangrui Meng] update doc 357575c [Xiangrui Meng] fix unit test 20b4816 [Xiangrui Meng] Merge branch 'master' into preserve-partitioner d1caa65 [Xiangrui Meng] add doc to explain preservesPartitioning fix wrong usage of preservesPartitioning make sample preserse partitioning
* [SPARK-2612] [mllib] Fix data skew in ALSpeng.zhang2014-07-221-6/+5
| | | | | | | | | Author: peng.zhang <peng.zhang@xiaomi.com> Closes #1521 from renozhang/fix-als and squashes the following commits: b5727a4 [peng.zhang] Remove no need argument 1a4f7a0 [peng.zhang] Fix data skew in ALS
* [SPARK-2495][MLLIB] remove private[mllib] from linear models' constructorsXiangrui Meng2014-07-205-5/+5
| | | | | | | | | | This is part of SPARK-2495 to allow users construct linear models manually. Author: Xiangrui Meng <meng@databricks.com> Closes #1492 from mengxr/public-constructor and squashes the following commits: a48b766 [Xiangrui Meng] remove private[mllib] from linear models' constructors
* [SPARK-2359][MLlib] CorrelationsDoris Xin2014-07-185-0/+519
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | Implementation for Pearson and Spearman's correlation. Author: Doris Xin <doris.s.xin@gmail.com> Closes #1367 from dorx/correlation and squashes the following commits: c0dd7dc [Doris Xin] here we go 32d83a3 [Doris Xin] Reviewer comments 4db0da1 [Doris Xin] added private[stat] to Spearman b716f70 [Doris Xin] minor fixes 6e1b42a [Doris Xin] More comments addressed. Still some open questions 8104f44 [Doris Xin] addressed comments. some open questions still 39387c2 [Doris Xin] added missing header bd3cf19 [Doris Xin] Merge branch 'master' into correlation 6341884 [Doris Xin] race condition bug squished bd2bacf [Doris Xin] Race condition bug b775ff9 [Doris Xin] old wrong impl 534ebf2 [Doris Xin] Merge branch 'master' into correlation 818fa31 [Doris Xin] wip units 9d808ee [Doris Xin] wip units b843a13 [Doris Xin] revert change in stat counter 28561b6 [Doris Xin] wip bb2e977 [Doris Xin] minor fix 8e02c63 [Doris Xin] Merge branch 'master' into correlation 2a40aa1 [Doris Xin] initial, untested implementation of Pearson dfc4854 [Doris Xin] WIP
* [MLlib] SPARK-1536: multiclass classification support for decision treeManish Amde2014-07-189-247/+898
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | The ability to perform multiclass classification is a big advantage for using decision trees and was a highly requested feature for mllib. This pull request adds multiclass classification support to the MLlib decision tree. It also adds sample weights support using WeightedLabeledPoint class for handling unbalanced datasets during classification. It will also support algorithms such as AdaBoost which requires instances to be weighted. It handles the special case where the categorical variables cannot be ordered for multiclass classification and thus the optimizations used for speeding up binary classification cannot be directly used for multiclass classification with categorical variables. More specifically, for m categories in a categorical feature, it analyses all the ```2^(m-1) - 1``` categorical splits provided that #splits are less than the maxBins provided in the input. This condition will not be met for features with large number of categories -- using decision trees is not recommended for such datasets in general since the categorical features are favored over continuous features. Moreover, the user can use a combination of tricks (increasing bin size of the tree algorithms, use binary encoding for categorical features or use one-vs-all classification strategy) to avoid these constraints. The new code is accompanied by unit tests and has also been tested on the iris and covtype datasets. cc: mengxr, etrain, hirakendu, atalwalkar, srowen Author: Manish Amde <manish9ue@gmail.com> Author: manishamde <manish9ue@gmail.com> Author: Evan Sparks <sparks@cs.berkeley.edu> Closes #886 from manishamde/multiclass and squashes the following commits: 26f8acc [Manish Amde] another attempt at fixing mima c5b2d04 [Manish Amde] more MIMA fixes 1ce7212 [Manish Amde] change problem filter for mima 10fdd82 [Manish Amde] fixing MIMA excludes e1c970d [Manish Amde] merged master abf2901 [Manish Amde] adding classes to MimaExcludes.scala 45e767a [Manish Amde] adding developer api annotation for overriden methods c8428c4 [Manish Amde] fixing weird multiline bug afced16 [Manish Amde] removed label weights support 2d85a48 [Manish Amde] minor: fixed scalastyle issues reprise 4e85f2c [Manish Amde] minor: fixed scalastyle issues b2ae41f [Manish Amde] minor: scalastyle e4c1321 [Manish Amde] using while loop for regression histograms d75ac32 [Manish Amde] removed WeightedLabeledPoint from this PR 0fecd38 [Manish Amde] minor: add newline to EOF 2061cf5 [Manish Amde] merged from master 06b1690 [Manish Amde] fixed off-by-one error in bin to split conversion 9cc3e31 [Manish Amde] added implicit conversion import 5c1b2ca [Manish Amde] doc for PointConverter class 485eaae [Manish Amde] implicit conversion from LabeledPoint to WeightedLabeledPoint 3d7f911 [Manish Amde] updated doc 8e44ab8 [Manish Amde] updated doc adc7315 [Manish Amde] support ordered categorical splits for multiclass classification e3e8843 [Manish Amde] minor code formatting 23d4268 [Manish Amde] minor: another minor code style 34ee7b9 [Manish Amde] minor: code style 237762d [Manish Amde] renaming functions 12e6d0a [Manish Amde] minor: removing line in doc 9a90c93 [Manish Amde] Merge branch 'master' into multiclass 1892a2c [Manish Amde] tests and use multiclass binaggregate length when atleast one categorical feature is present f5f6b83 [Manish Amde] multiclass for continous variables 8cfd3b6 [Manish Amde] working for categorical multiclass classification 828ff16 [Manish Amde] added categorical variable test bce835f [Manish Amde] code cleanup 7e5f08c [Manish Amde] minor doc 1dd2735 [Manish Amde] bin search logic for multiclass f16a9bb [Manish Amde] fixing while loop d811425 [Manish Amde] multiclass bin aggregate logic ab5cb21 [Manish Amde] multiclass logic d8e4a11 [Manish Amde] sample weights ed5a2df [Manish Amde] fixed classification requirements d012be7 [Manish Amde] fixed while loop 18d2835 [Manish Amde] changing default values for num classes 6b912dc [Manish Amde] added numclasses to tree runner, predict logic for multiclass, add multiclass option to train 75f2bfc [Manish Amde] minor code style fix e547151 [Manish Amde] minor modifications 34549d0 [Manish Amde] fixing error during merge 098e8c5 [Manish Amde] merged master e006f9d [Manish Amde] changing variable names 5c78e1a [Manish Amde] added multiclass support 6c7af22 [Manish Amde] prepared for multiclass without breaking binary classification 46e06ee [Manish Amde] minor mods 3f85a17 [Manish Amde] tests for multiclass classification 4d5f70c [Manish Amde] added multiclass support for find splits bins 46f909c [Manish Amde] todo for multiclass support 455bea9 [Manish Amde] fixed tests 14aea48 [Manish Amde] changing instance format to weighted labeled point a1a6e09 [Manish Amde] added weighted point class 968ca9d [Manish Amde] merged master 7fc9545 [Manish Amde] added docs ce004a1 [Manish Amde] minor formatting b27ad2c [Manish Amde] formatting 426bb28 [Manish Amde] programming guide blurb 8053fed [Manish Amde] more formatting 5eca9e4 [Manish Amde] grammar 4731cda [Manish Amde] formatting 5e82202 [Manish Amde] added documentation, fixed off by 1 error in max level calculation cbd9f14 [Manish Amde] modified scala.math to math dad9652 [Manish Amde] removed unused imports e0426ee [Manish Amde] renamed parameter 718506b [Manish Amde] added unit test 1517155 [Manish Amde] updated documentation 9dbdabe [Manish Amde] merge from master 719d009 [Manish Amde] updating user documentation fecf89a [manishamde] Merge pull request #6 from etrain/deep_tree 0287772 [Evan Sparks] Fixing scalastyle issue. 2f1e093 [Manish Amde] minor: added doc for maxMemory parameter 2f6072c [manishamde] Merge pull request #5 from etrain/deep_tree abc5a23 [Evan Sparks] Parameterizing max memory. 50b143a [Manish Amde] adding support for very deep trees
* SPARK-1215 [MLLIB]: Clustering: Index out of bounds error (2)Joseph K. Bradley2014-07-172-1/+33
| | | | | | | | | | | Added check to LocalKMeans.scala: kMeansPlusPlus initialization to handle case with fewer distinct data points than clusters k. Added two related unit tests to KMeansSuite. (Re-submitting PR after tangling commits in PR 1407 https://github.com/apache/spark/pull/1407 ) Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com> Closes #1468 from jkbradley/kmeans-fix and squashes the following commits: 4e9bd1e [Joseph K. Bradley] Updated PR per comments from mengxr 6c7a2ec [Joseph K. Bradley] Added check to LocalKMeans.scala: kMeansPlusPlus initialization to handle case with fewer distinct data points than clusters k. Added two related unit tests to KMeansSuite.
* [MLLIB] [SPARK-2222] Add multiclass evaluation metricsAlexander Ulanov2014-07-152-0/+280
| | | | | | | | | | | | | | | | | | | | | | | | | | | | Adding two classes: 1) MulticlassMetrics implements various multiclass evaluation metrics 2) MulticlassMetricsSuite implements unit tests for MulticlassMetrics Author: Alexander Ulanov <nashb@yandex.ru> Author: unknown <ulanov@ULANOV1.emea.hpqcorp.net> Author: Xiangrui Meng <meng@databricks.com> Closes #1155 from avulanov/master and squashes the following commits: 2eae80f [Alexander Ulanov] Merge pull request #1 from mengxr/avulanov-master 5ebeb08 [Xiangrui Meng] minor updates 79c3555 [Alexander Ulanov] Addressing reviewers comments mengxr 0fa9511 [Alexander Ulanov] Addressing reviewers comments mengxr f0dadc9 [Alexander Ulanov] Addressing reviewers comments mengxr 4811378 [Alexander Ulanov] Removing println 87fb11f [Alexander Ulanov] Addressing reviewers comments mengxr. Added confusion matrix e3db569 [Alexander Ulanov] Addressing reviewers comments mengxr. Added true positive rate and false positive rate. Test suite code style. a7e8bf0 [Alexander Ulanov] Addressing reviewers comments mengxr c3a77ad [Alexander Ulanov] Addressing reviewers comments mengxr e2c91c3 [Alexander Ulanov] Fixes to mutliclass metics d5ce981 [unknown] Comments about Double a5c8ba4 [unknown] Unit tests. Class rename fcee82d [unknown] Unit tests. Class rename d535d62 [unknown] Multiclass evaluation
* [SPARK-2477][MLlib] Using appendBias for adding intercept in ↵DB Tsai2014-07-151-16/+5
| | | | | | | | | | | | GeneralizedLinearAlgorithm Instead of using prependOne currently in GeneralizedLinearAlgorithm, we would like to use appendBias for 1) keeping the indices of original training set unchanged by adding the intercept into the last element of vector and 2) using the same public API for consistently adding intercept. Author: DB Tsai <dbtsai@alpinenow.com> Closes #1410 from dbtsai/SPARK-2477_intercept_with_appendBias and squashes the following commits: 011432c [DB Tsai] From Alpine Data Labs
* SPARK-2363. Clean MLlib's sample data filesSean Owen2014-07-137-2080/+0
| | | | | | | | | | | | | | | | (Just made a PR for this, mengxr was the reporter of:) MLlib has sample data under serveral folders: 1) data/mllib 2) data/ 3) mllib/data/* Per previous discussion with Matei Zaharia, we want to put them under `data/mllib` and clean outdated files. Author: Sean Owen <sowen@cloudera.com> Closes #1394 from srowen/SPARK-2363 and squashes the following commits: 54313dd [Sean Owen] Move ML example data from /mllib/data/ and /data/ into /data/mllib/
* SPARK-2462. Make Vector.apply public.Sandy Ryza2014-07-121-1/+1
| | | | | | | | | | Apologies if there's an already-discussed reason I missed for why this doesn't make sense. Author: Sandy Ryza <sandy@cloudera.com> Closes #1389 from sryza/sandy-spark-2462 and squashes the following commits: 2e5e201 [Sandy Ryza] SPARK-2462. Make Vector.apply public.
* use specialized axpy in RowMatrix for SVDLi Pu2014-07-111-1/+7
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | After running some more tests on large matrix, found that the BV axpy (breeze/linalg/Vector.scala, axpy) is slower than the BSV axpy (breeze/linalg/operators/SparseVectorOps.scala, sv_dv_axpy), 8s v.s. 2s for each multiplication. The BV axpy operates on an iterator while BSV axpy directly operates on the underlying array. I think the overhead comes from creating the iterator (with a zip) and advancing the pointers. Author: Li Pu <lpu@twitter.com> Author: Xiangrui Meng <meng@databricks.com> Author: Li Pu <li.pu@outlook.com> Closes #1378 from vrilleup/master and squashes the following commits: 6fb01a3 [Li Pu] use specialized axpy in RowMatrix 5255f2a [Li Pu] Merge remote-tracking branch 'upstream/master' 7312ec1 [Li Pu] very minor comment fix 4c618e9 [Li Pu] Merge pull request #1 from mengxr/vrilleup-master a461082 [Xiangrui Meng] make superscript show up correctly in doc 861ec48 [Xiangrui Meng] simplify axpy 62969fa [Xiangrui Meng] use BDV directly in symmetricEigs change the computation mode to local-svd, local-eigs, and dist-eigs update tests and docs c273771 [Li Pu] automatically determine SVD compute mode and parameters 7148426 [Li Pu] improve RowMatrix multiply 5543cce [Li Pu] improve svd api 819824b [Li Pu] add flag for dense svd or sparse svd eb15100 [Li Pu] fix binary compatibility 4c7aec3 [Li Pu] improve comments e7850ed [Li Pu] use aggregate and axpy 827411b [Li Pu] fix EOF new line 9c80515 [Li Pu] use non-sparse implementation when k = n fe983b0 [Li Pu] improve scala style 96d2ecb [Li Pu] improve eigenvalue sorting e1db950 [Li Pu] SPARK-1782: svd for sparse matrix using ARPACK
* [SPARK-1969][MLlib] Online summarizer APIs for mean, variance, min, and maxDB Tsai2014-07-114-134/+457
| | | | | | | | | | | | | | | | It basically moved the private ColumnStatisticsAggregator class from RowMatrix to public available DeveloperApi with documentation and unitests. Changes: 1) Moved the private implementation from org.apache.spark.mllib.linalg.ColumnStatisticsAggregator to org.apache.spark.mllib.stat.MultivariateOnlineSummarizer 2) When creating OnlineSummarizer object, the number of columns is not needed in the constructor. It's determined when users add the first sample. 3) Added the APIs documentation for MultivariateOnlineSummarizer. 4) Added the unittests for MultivariateOnlineSummarizer. Author: DB Tsai <dbtsai@dbtsai.com> Closes #955 from dbtsai/dbtsai-summarizer and squashes the following commits: b13ac90 [DB Tsai] dbtsai-summarizer
* [SPARK-2358][MLLIB] Add an option to include native BLAS/LAPACK loader in ↵Xiangrui Meng2014-07-101-0/+13
| | | | | | | | | | | | the build It would be easy for users to include the netlib-java jniloader in the spark jar, which is LGPL-licensed. We can follow the same approach as ganglia support in Spark, which could be enabled by turning on "-Pganglia-lgpl" at build time. We can use "-Pnetlib-lgpl" flag for this. Author: Xiangrui Meng <meng@databricks.com> Closes #1295 from mengxr/netlib-lgpl and squashes the following commits: aebf001 [Xiangrui Meng] add a profile to optionally include native BLAS/LAPACK loader in mllib
* [SPARK-1776] Have Spark's SBT build read dependencies from Maven.Prashant Sharma2014-07-101-0/+3
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Patch introduces the new way of working also retaining the existing ways of doing things. For example build instruction for yarn in maven is `mvn -Pyarn -PHadoop2.2 clean package -DskipTests` in sbt it can become `MAVEN_PROFILES="yarn, hadoop-2.2" sbt/sbt clean assembly` Also supports `sbt/sbt -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 clean assembly` Author: Prashant Sharma <prashant.s@imaginea.com> Author: Patrick Wendell <pwendell@gmail.com> Closes #772 from ScrapCodes/sbt-maven and squashes the following commits: a8ac951 [Prashant Sharma] Updated sbt version. 62b09bb [Prashant Sharma] Improvements. fa6221d [Prashant Sharma] Excluding sql from mima 4b8875e [Prashant Sharma] Sbt assembly no longer builds tools by default. 72651ca [Prashant Sharma] Addresses code reivew comments. acab73d [Prashant Sharma] Revert "Small fix to run-examples script." ac4312c [Prashant Sharma] Revert "minor fix" 6af91ac [Prashant Sharma] Ported oldDeps back. + fixes issues with prev commit. 65cf06c [Prashant Sharma] Servelet API jars mess up with the other servlet jars on the class path. 446768e [Prashant Sharma] minor fix 89b9777 [Prashant Sharma] Merge conflicts d0a02f2 [Prashant Sharma] Bumped up pom versions, Since the build now depends on pom it is better updated there. + general cleanups. dccc8ac [Prashant Sharma] updated mima to check against 1.0 a49c61b [Prashant Sharma] Fix for tools jar a2f5ae1 [Prashant Sharma] Fixes a bug in dependencies. cf88758 [Prashant Sharma] cleanup 9439ea3 [Prashant Sharma] Small fix to run-examples script. 96cea1f [Prashant Sharma] SPARK-1776 Have Spark's SBT build read dependencies from Maven. 36efa62 [Patrick Wendell] Set project name in pom files and added eclipse/intellij plugins. 4973dbd [Patrick Wendell] Example build using pom reader.
* SPARK-1782: svd for sparse matrix using ARPACKLi Pu2014-07-093-60/+339
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | copy ARPACK dsaupd/dseupd code from latest breeze change RowMatrix to use sparse SVD change tests for sparse SVD All tests passed. I will run it against some large matrices. Author: Li Pu <lpu@twitter.com> Author: Xiangrui Meng <meng@databricks.com> Author: Li Pu <li.pu@outlook.com> Closes #964 from vrilleup/master and squashes the following commits: 7312ec1 [Li Pu] very minor comment fix 4c618e9 [Li Pu] Merge pull request #1 from mengxr/vrilleup-master a461082 [Xiangrui Meng] make superscript show up correctly in doc 861ec48 [Xiangrui Meng] simplify axpy 62969fa [Xiangrui Meng] use BDV directly in symmetricEigs change the computation mode to local-svd, local-eigs, and dist-eigs update tests and docs c273771 [Li Pu] automatically determine SVD compute mode and parameters 7148426 [Li Pu] improve RowMatrix multiply 5543cce [Li Pu] improve svd api 819824b [Li Pu] add flag for dense svd or sparse svd eb15100 [Li Pu] fix binary compatibility 4c7aec3 [Li Pu] improve comments e7850ed [Li Pu] use aggregate and axpy 827411b [Li Pu] fix EOF new line 9c80515 [Li Pu] use non-sparse implementation when k = n fe983b0 [Li Pu] improve scala style 96d2ecb [Li Pu] improve eigenvalue sorting e1db950 [Li Pu] SPARK-1782: svd for sparse matrix using ARPACK
* [SPARK-2417][MLlib] Fix DecisionTree testsjohnnywalleye2014-07-091-4/+4
| | | | | | | | | | | | | | | Fixes test failures introduced by https://github.com/apache/spark/pull/1316. For both the regression and classification cases, val stats is the InformationGainStats for the best tree split. stats.predict is the predicted value for the data, before the split is made. Since 600 of the 1,000 values generated by DecisionTreeSuite.generateCategoricalDataPoints() are 1.0 and the rest 0.0, the regression tree and classification tree both correctly predict a value of 0.6 for this data now, and the assertions have been changed to reflect that. Author: johnnywalleye <jsondag@gmail.com> Closes #1343 from johnnywalleye/decision-tree-tests and squashes the following commits: ef80603 [johnnywalleye] [SPARK-2417][MLlib] Fix DecisionTree tests
* [SPARK-2152][MLlib] fix bin offset in DecisionTree node aggregations (also ↵johnnywalleye2014-07-081-5/+5
| | | | | | | | | | | | | | | | | | | | | | | | | | | resolves SPARK-2160) Hi, this pull fixes (what I believe to be) a bug in DecisionTree.scala. In the extractLeftRightNodeAggregates function, the first set of rightNodeAgg values for Regression are set in line 792 as follows: rightNodeAgg(featureIndex)(2 * (numBins - 2)) = binData(shift + (2 * numBins - 1))) Then there is a loop that sets the rest of the values, as in line 809: rightNodeAgg(featureIndex)(2 * (numBins - 2 - splitIndex)) = binData(shift + (2 *(numBins - 2 - splitIndex))) + rightNodeAgg(featureIndex)(2 * (numBins - 1 - splitIndex)) But since splitIndex starts at 1, this ends up skipping a set of binData values. The changes here address this issue, for both the Regression and Classification cases. Author: johnnywalleye <jsondag@gmail.com> Closes #1316 from johnnywalleye/master and squashes the following commits: 73809da [johnnywalleye] fix bin offset in DecisionTree node aggregations
* SPARK-1675. Make clear whether computePrincipalComponents requires centered dataSean Owen2014-07-031-0/+2
| | | | | | | | | | Just closing out this small JIRA, resolving with a comment change. Author: Sean Owen <sowen@cloudera.com> Closes #1171 from srowen/SPARK-1675 and squashes the following commits: 45ee9b7 [Sean Owen] Add simple note that data need not be centered for computePrincipalComponents
* [SPARK-2172] PySpark cannot import mllib modules in YARN-client modeSzul, Piotr2014-06-251-0/+8
| | | | | | | | | | | | | | | Include pyspark/mllib python sources as resources in the mllib.jar. This way they will be included in the final assembly Author: Szul, Piotr <Piotr.Szul@csiro.au> Closes #1223 from piotrszul/branch-1.0 and squashes the following commits: 69d5174 [Szul, Piotr] Removed unsed resource directory src/main/resource from mllib pom f8c52a0 [Szul, Piotr] [SPARK-2172] PySpark cannot import mllib modules in YARN-client mode Include pyspark/mllib python sources as resources in the jar (cherry picked from commit fa167194ce1b5898e4d7232346c9f86b2897a722) Signed-off-by: Reynold Xin <rxin@apache.org>
* [SPARK-2163] class LBFGS optimize with Double tolerance instead of IntGang Bai2014-06-202-1/+35
| | | | | | | | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-2163 This pull request includes the change for **[SPARK-2163]**: * Changed the convergence tolerance parameter from type `Int` to type `Double`. * Added types for vars in `class LBFGS`, making the style consistent with `class GradientDescent`. * Added associated test to check that optimizing via `class LBFGS` produces the same results as via calling `runLBFGS` from `object LBFGS`. This is a very minor change but it will solve the problem in my implementation of a regression model for count data, where I make use of LBFGS for parameter estimation. Author: Gang Bai <me@baigang.net> Closes #1104 from BaiGang/fix_int_tol and squashes the following commits: cecf02c [Gang Bai] Changed setConvergenceTol'' to specify tolerance with a parameter of type Double. For the reason and the problem caused by an Int parameter, please check https://issues.apache.org/jira/browse/SPARK-2163. Added a test in LBFGSSuite for validating that optimizing via class LBFGS produces the same results as calling runLBFGS from object LBFGS. Keep the indentations and styles correct.
* Squishing a typo bug before it causes real harmDoris Xin2014-06-181-1/+1
| | | | | | | | | | in updateNumRows method in RowMatrix Author: Doris Xin <doris.s.xin@gmail.com> Closes #1125 from dorx/updateNumRows and squashes the following commits: 8564aef [Doris Xin] Squishing a typo bug before it causes real harm
* SPARK-2085: [MLlib] Apply user-specific regularization instead of uniform ↵Shuo Xiang2014-06-121-1/+7
| | | | | | | | | | | | | | regularization in ALS The current implementation of ALS takes a single regularization parameter and apply it on both of the user factors and the product factors. This kind of regularization can be less effective while user number is significantly larger than the number of products (and vice versa). For example, if we have 10M users and 1K product, regularization on user factors will dominate. Following the discussion in [this thread](http://apache-spark-user-list.1001560.n3.nabble.com/possible-bug-in-Spark-s-ALS-implementation-tt2567.html#a2704), the implementation in this PR will regularize each factor vector by #ratings * lambda. Author: Shuo Xiang <sxiang@twitter.com> Closes #1026 from coderxiang/als-reg and squashes the following commits: 93dfdb4 [Shuo Xiang] Merge remote-tracking branch 'upstream/master' into als-reg b98f19c [Shuo Xiang] merge latest master 52c7b58 [Shuo Xiang] Apply user-specific regularization instead of uniform regularization in Alternating Least Squares (ALS)
* [SPARK-1672][MLLIB] Separate user and product partitioning in ALSTor Myklebust2014-06-112-83/+141
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Some clean up work following #593. 1. Allow to set different number user blocks and number product blocks in `ALS`. 2. Update `MovieLensALS` to reflect the change. Author: Tor Myklebust <tmyklebu@gmail.com> Author: Xiangrui Meng <meng@databricks.com> Closes #1014 from mengxr/SPARK-1672 and squashes the following commits: 0e910dd [Xiangrui Meng] change private[this] to private[recommendation] 36420c7 [Xiangrui Meng] set exclusion rules for ALS 9128b77 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-1672 294efe9 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-1672 9bab77b [Xiangrui Meng] clean up add numUserBlocks and numProductBlocks to MovieLensALS 84c8e8c [Xiangrui Meng] Merge branch 'master' into SPARK-1672 d17a8bf [Xiangrui Meng] merge master a4925fd [Tor Myklebust] Style. bd8a75c [Tor Myklebust] Merge branch 'master' of github.com:apache/spark into alsseppar 021f54b [Tor Myklebust] Separate user and product blocks. dcf583a [Tor Myklebust] Remove the partitioner member variable; instead, thread that needle everywhere it needs to go. 23d6f91 [Tor Myklebust] Stop making the partitioner configurable. 495784f [Tor Myklebust] Merge branch 'master' of https://github.com/apache/spark 674933a [Tor Myklebust] Fix style. 40edc23 [Tor Myklebust] Fix missing space. f841345 [Tor Myklebust] Fix daft bug creating 'pairs', also for -> foreach. 5ec9e6c [Tor Myklebust] Clean a couple of things up using 'map'. 36a0f43 [Tor Myklebust] Make the partitioner private. d872b09 [Tor Myklebust] Add negative id ALS test. df27697 [Tor Myklebust] Support custom partitioners. Currently we use the same partitioner for users and products. c90b6d8 [Tor Myklebust] Scramble user and product ids before bucketing. c774d7d [Tor Myklebust] Make the partitioner a member variable and use it instead of modding directly.
* Resolve scalatest warnings during buildwitgo2014-06-103-6/+6
| | | | | | | | Author: witgo <witgo@qq.com> Closes #1032 from witgo/ShouldMatchers and squashes the following commits: 7ebf34c [witgo] Resolve scalatest warnings during build
* Remove compile-scoped junit dependency.Marcelo Vanzin2014-06-051-0/+8
| | | | | | | | | | | | | This avoids having junit classes showing up in the assembly jar. I verified that only test classes in the jtransforms package use junit. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #794 from vanzin/junit-dep-exclusion and squashes the following commits: 274e1c2 [Marcelo Vanzin] Remove junit from assembly in sbt build also. ad950be [Marcelo Vanzin] Remove compile-scoped junit dependency.
* [SPARK-2029] Bump pom.xml version number of master branch to 1.1.0-SNAPSHOT.Takuya UESHIN2014-06-051-1/+1
| | | | | | | | Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #974 from ueshin/issues/SPARK-2029 and squashes the following commits: e19e8f4 [Takuya UESHIN] Bump version number to 1.1.0-SNAPSHOT.
* [SPARK-1752][MLLIB] Standardize text format for vectors and labeled pointsXiangrui Meng2014-06-0413-20/+449
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | We should standardize the text format used to represent vectors and labeled points. The proposed formats are the following: 1. dense vector: `[v0,v1,..]` 2. sparse vector: `(size,[i0,i1],[v0,v1])` 3. labeled point: `(label,vector)` where "(..)" indicates a tuple and "[...]" indicate an array. `loadLabeledPoints` is added to pyspark's `MLUtils`. I didn't add `loadVectors` to pyspark because `RDD.saveAsTextFile` cannot stringify dense vectors in the proposed format automatically. `MLUtils#saveLabeledData` and `MLUtils#loadLabeledData` are deprecated. Users should use `RDD#saveAsTextFile` and `MLUtils#loadLabeledPoints` instead. In Scala, `MLUtils#loadLabeledPoints` is compatible with the format used by `MLUtils#loadLabeledData`. CC: @mateiz, @srowen Author: Xiangrui Meng <meng@databricks.com> Closes #685 from mengxr/labeled-io and squashes the following commits: 2d1116a [Xiangrui Meng] make loadLabeledData/saveLabeledData deprecated since 1.0.1 297be75 [Xiangrui Meng] change LabeledPoint.parse to LabeledPointParser.parse to maintain binary compatibility d6b1473 [Xiangrui Meng] Merge branch 'master' into labeled-io 56746ea [Xiangrui Meng] replace # by . 623a5f0 [Xiangrui Meng] merge master f06d5ba [Xiangrui Meng] add docs and minor updates 640fe0c [Xiangrui Meng] throw SparkException 5bcfbc4 [Xiangrui Meng] update test to add scientific notations e86bf38 [Xiangrui Meng] remove NumericTokenizer 050fca4 [Xiangrui Meng] use StringTokenizer 6155b75 [Xiangrui Meng] merge master f644438 [Xiangrui Meng] remove parse methods based on eval from pyspark a41675a [Xiangrui Meng] python loadLabeledPoint uses Scala's implementation ce9a475 [Xiangrui Meng] add deserialize_labeled_point to pyspark with tests e9fcd49 [Xiangrui Meng] add serializeLabeledPoint and tests aea4ae3 [Xiangrui Meng] minor updates 810d6df [Xiangrui Meng] update tokenizer/parser implementation 7aac03a [Xiangrui Meng] remove Scala parsers c1885c1 [Xiangrui Meng] add headers and minor changes b0c50cb [Xiangrui Meng] add customized parser d731817 [Xiangrui Meng] style update 63dc396 [Xiangrui Meng] add loadLabeledPoints to pyspark ea122b5 [Xiangrui Meng] Merge branch 'master' into labeled-io cd6c78f [Xiangrui Meng] add __str__ and parse to LabeledPoint a7a178e [Xiangrui Meng] add stringify to pyspark's Vectors 5c2dbfa [Xiangrui Meng] add parse to pyspark's Vectors 7853f88 [Xiangrui Meng] update pyspark's SparseVector.__str__ e761d32 [Xiangrui Meng] make LabelPoint.parse compatible with the dense format used before v1.0 and deprecate loadLabeledData and saveLabeledData 9e63a02 [Xiangrui Meng] add loadVectors and loadLabeledPoints 19aa523 [Xiangrui Meng] update toString and add parsers for Vectors and LabeledPoint
* [MLLIB] set RDD names in ALSNeville Li2014-06-041-5/+11
| | | | | | | | | | | This is very useful when debugging & fine tuning jobs with large data sets. Author: Neville Li <neville@spotify.com> Closes #966 from nevillelyh/master and squashes the following commits: 6747764 [Neville Li] [MLLIB] use string interpolation for RDD names 3b15d34 [Neville Li] [MLLIB] set RDD names in ALS
* Fixed a typoDB Tsai2014-06-031-1/+1
| | | | | | | | | | in RowMatrix.scala Author: DB Tsai <dbtsai@dbtsai.com> Closes #959 from dbtsai/dbtsai-typo and squashes the following commits: fab0e0e [DB Tsai] Fixed typo
* [SPARK-1942] Stop clearing spark.driver.port in unit testsSyed Hashmi2014-06-039-9/+0
| | | | | | | | | | | | | | | | | | | stop resetting spark.driver.port in unit tests (scala, java and python). Author: Syed Hashmi <shashmi@cloudera.com> Author: CodingCat <zhunansjtu@gmail.com> Closes #943 from syedhashmi/master and squashes the following commits: 885f210 [Syed Hashmi] Removing unnecessary file (created by mergetool) b8bd4b5 [Syed Hashmi] Merge remote-tracking branch 'upstream/master' b895e59 [Syed Hashmi] Revert "[SPARK-1784] Add a new partitioner" 57b6587 [Syed Hashmi] Revert "[SPARK-1784] Add a balanced partitioner" 1574769 [Syed Hashmi] [SPARK-1942] Stop clearing spark.driver.port in unit tests 4354836 [Syed Hashmi] Revert "SPARK-1686: keep schedule() calling in the main thread" fd36542 [Syed Hashmi] [SPARK-1784] Add a balanced partitioner 6668015 [CodingCat] SPARK-1686: keep schedule() calling in the main thread 4ca94cc [Syed Hashmi] [SPARK-1784] Add a new partitioner
* [SPARK-1553] Alternating nonnegative least-squaresTor Myklebust2014-06-024-14/+300
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This pull request includes a nonnegative least-squares solver (NNLS) tailored to the kinds of small-scale problems that come up when training matrix factorisation models by alternating nonnegative least-squares (ANNLS). The method used for the NNLS subproblems is based on the classical method of projected gradients. There is a modification where, if the set of active constraints has not changed since the last iteration, a conjugate gradient step is considered and possibly rejected in favour of the gradient; this improves convergence once the optimal face has been located. The NNLS solver is in `org.apache.spark.mllib.optimization.NNLSbyPCG`. Author: Tor Myklebust <tmyklebu@gmail.com> Closes #460 from tmyklebu/annls and squashes the following commits: 79bc4b5 [Tor Myklebust] Merge branch 'master' of https://github.com/apache/spark into annls 199b0bc [Tor Myklebust] Make the ctor private again and use the builder pattern. 7fbabf1 [Tor Myklebust] Cleanup matrix math in NNLSSuite. 65ef7f2 [Tor Myklebust] Make ALS's ctor public and remove a couple of "convenience" wrappers. 2d4f3cb [Tor Myklebust] Cleanup. 0cb4481 [Tor Myklebust] Drop the iteration limit from 40k to max(400,20n). e2a01d1 [Tor Myklebust] Create a workspace object for NNLS to cut down on memory allocations. b285106 [Tor Myklebust] Clean up NNLS test cases. 9c820b6 [Tor Myklebust] Tweak variable names. 8a1a436 [Tor Myklebust] Describe the problem and add a reference to Polyak's paper. 5345402 [Tor Myklebust] Style fixes that got eaten. ac673bd [Tor Myklebust] More safeguards against numerical ridiculousness. c288b6a [Tor Myklebust] Finish moving the NNLS solver. 9a82fa6 [Tor Myklebust] Fix scalastyle moanings. 33bf4f2 [Tor Myklebust] Fix missing space. 89ea0a8 [Tor Myklebust] Hack ALSSuite to support NNLS testing. f5dbf4d [Tor Myklebust] Teach ALS how to use the NNLS solver. 6cb563c [Tor Myklebust] Tests for the nonnegative least squares solver. a68ac10 [Tor Myklebust] A nonnegative least-squares solver.
* SPARK-1925: Replace '&' with '&&'zsxwing2014-05-261-2/+2
| | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-1925 Author: zsxwing <zsxwing@gmail.com> Closes #879 from zsxwing/SPARK-1925 and squashes the following commits: 5cf5a6d [zsxwing] SPARK-1925: Replace '&' with '&&'
* Update LBFGSSuite.scalabaishuo(白硕)2014-05-231-2/+2
| | | | | | | | | | the same reason as https://github.com/apache/spark/pull/588 Author: baishuo(白硕) <vc_java@hotmail.com> Closes #815 from baishuo/master and squashes the following commits: 6876c1e [baishuo(白硕)] Update LBFGSSuite.scala
* [SPARK-1741][MLLIB] add predict(JavaRDD) to RegressionModel, ↵Xiangrui Meng2014-05-156-2/+76
| | | | | | | | | | | | | | | | | | | ClassificationModel, and KMeans `model.predict` returns a RDD of Scala primitive type (Int/Double), which is recognized as Object in Java. Adding predict(JavaRDD) could make life easier for Java users. Added tests for KMeans, LinearRegression, and NaiveBayes. Will update examples after https://github.com/apache/spark/pull/653 gets merged. cc: @srowen Author: Xiangrui Meng <meng@databricks.com> Closes #670 from mengxr/predict-javardd and squashes the following commits: b77ccd8 [Xiangrui Meng] Merge branch 'master' into predict-javardd 43caac9 [Xiangrui Meng] add predict(JavaRDD) to RegressionModel, ClassificationModel, and KMeans
* Package docsPrashant Sharma2014-05-143-0/+69
| | | | | | | | | | | | | | This is a few changes based on the original patch by @scrapcodes. Author: Prashant Sharma <prashant.s@imaginea.com> Author: Patrick Wendell <pwendell@gmail.com> Closes #785 from pwendell/package-docs and squashes the following commits: c32b731 [Patrick Wendell] Changes based on Prashant's patch c0463d3 [Prashant Sharma] added eof new line ce8bf73 [Prashant Sharma] Added eof new line to all files. 4c35f2e [Prashant Sharma] SPARK-1563 Add package-info.java and package.scala files for all packages that appear in docs
* [SPARK-1696][MLLIB] use alpha in dense dsprXiangrui Meng2014-05-141-1/+1
| | | | | | | | | | It doesn't affect existing code because only `alpha = 1.0` is used in the code. Author: Xiangrui Meng <meng@databricks.com> Closes #778 from mengxr/mllib-dspr-fix and squashes the following commits: a37402e [Xiangrui Meng] use alpha in dense dspr
* SPARK-1791 - SVM implementation does not use threshold parameterAndrew Tulloch2014-05-132-1/+38
| | | | | | | | | | | | | | | | | | | | | | | | Summary: https://issues.apache.org/jira/browse/SPARK-1791 Simple fix, and backward compatible, since - anyone who set the threshold was getting completely wrong answers. - anyone who did not set the threshold had the default 0.0 value for the threshold anyway. Test Plan: Unit test added that is verified to fail under the old implementation, and pass under the new implementation. Reviewers: CC: Author: Andrew Tulloch <andrew@tullo.ch> Closes #725 from ajtulloch/SPARK-1791-SVM and squashes the following commits: 770f55d [Andrew Tulloch] SPARK-1791 - SVM implementation does not use threshold parameter
* SPARK-1798. Tests should clean up temp filesSean Owen2014-05-122-14/+5
| | | | | | | | | | | | | | | | | | | | Three issues related to temp files that tests generate – these should be touched up for hygiene but are not urgent. Modules have a log4j.properties which directs the unit-test.log output file to a directory like `[module]/target/unit-test.log`. But this ends up creating `[module]/[module]/target/unit-test.log` instead of former. The `work/` directory is not deleted by "mvn clean", in the parent and in modules. Neither is the `checkpoint/` directory created under the various external modules. Many tests create a temp directory, which is not usually deleted. This can be largely resolved by calling `deleteOnExit()` at creation and trying to call `Utils.deleteRecursively` consistently to clean up, sometimes in an `@After` method. _If anyone seconds the motion, I can create a more significant change that introduces a new test trait along the lines of `LocalSparkContext`, which provides management of temp directories for subclasses to take advantage of._ Author: Sean Owen <sowen@cloudera.com> Closes #732 from srowen/SPARK-1798 and squashes the following commits: 5af578e [Sean Owen] Try to consistently delete test temp dirs and files, and set deleteOnExit() for each b21b356 [Sean Owen] Remove work/ and checkpoint/ dirs with mvn clean bdd0f41 [Sean Owen] Remove duplicate module dir in log4j.properties output path for tests
* Bug fix of sparse vector conversionFunes2014-05-082-1/+14
| | | | | | | | | | | | | | | Fixed a small bug caused by the inconsistency of index/data array size and vector length. Author: Funes <tianshaocun@gmail.com> Author: funes <tianshaocun@gmail.com> Closes #661 from funes/bugfix and squashes the following commits: edb2b9d [funes] remove unused import 75dced3 [Funes] update test case d129a66 [Funes] Add test for sparse breeze by vector builder 64e7198 [Funes] Copy data only when necessary b85806c [Funes] Bug fix of sparse vector conversion
* [SPARK-1157][MLlib] Bug fix: lossHistory should exclude rejection steps, and ↵DB Tsai2014-05-082-48/+30
| | | | | | | | | | | | | | remove miniBatch Getting the lossHistory from Breeze's API which already excludes the rejection steps in line search. Also, remove the miniBatch in LBFGS since those quasi-Newton methods approximate the inverse of Hessian. It doesn't make sense if the gradients are computed from a varying objective. Author: DB Tsai <dbtsai@alpinenow.com> Closes #582 from dbtsai/dbtsai-lbfgs-bug and squashes the following commits: 9cc6cf9 [DB Tsai] Removed the miniBatch in LBFGS. 1ba6a33 [DB Tsai] Formatting the code. d72c679 [DB Tsai] Using Breeze's states to get the loss.
* SPARK-1544 Add support for deep decision trees.Manish Amde2014-05-073-23/+170
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | @etrain and I came with a PR for arbitrarily deep decision trees at the cost of multiple passes over the data at deep tree levels. To summarize: 1) We take a parameter that indicates the amount of memory users want to reserve for computation on each worker (and 2x that at the driver). 2) Using that information, we calculate two things - the maximum depth to which we train as usual (which is, implicitly, the maximum number of nodes we want to train in parallel), and the size of the groups we should use in the case where we exceed this depth. cc: @atalwalkar, @hirakendu, @mengxr Author: Manish Amde <manish9ue@gmail.com> Author: manishamde <manish9ue@gmail.com> Author: Evan Sparks <sparks@cs.berkeley.edu> Closes #475 from manishamde/deep_tree and squashes the following commits: 968ca9d [Manish Amde] merged master 7fc9545 [Manish Amde] added docs ce004a1 [Manish Amde] minor formatting b27ad2c [Manish Amde] formatting 426bb28 [Manish Amde] programming guide blurb 8053fed [Manish Amde] more formatting 5eca9e4 [Manish Amde] grammar 4731cda [Manish Amde] formatting 5e82202 [Manish Amde] added documentation, fixed off by 1 error in max level calculation cbd9f14 [Manish Amde] modified scala.math to math dad9652 [Manish Amde] removed unused imports e0426ee [Manish Amde] renamed parameter 718506b [Manish Amde] added unit test 1517155 [Manish Amde] updated documentation 9dbdabe [Manish Amde] merge from master 719d009 [Manish Amde] updating user documentation fecf89a [manishamde] Merge pull request #6 from etrain/deep_tree 0287772 [Evan Sparks] Fixing scalastyle issue. 2f1e093 [Manish Amde] minor: added doc for maxMemory parameter 2f6072c [manishamde] Merge pull request #5 from etrain/deep_tree abc5a23 [Evan Sparks] Parameterizing max memory. 50b143a [Manish Amde] adding support for very deep trees
* Update GradientDescentSuite.scalabaishuo(白硕)2014-05-071-3/+3
| | | | | | | | | | | | use more faster way to construct an array Author: baishuo(白硕) <vc_java@hotmail.com> Closes #588 from baishuo/master and squashes the following commits: 45b95fb [baishuo(白硕)] Update GradientDescentSuite.scala c03b61c [baishuo(白硕)] Update GradientDescentSuite.scala b666d27 [baishuo(白硕)] Update GradientDescentSuite.scala
* SPARK-1727. Correct small compile errors, typos, and markdown issues in ↵Sean Owen2014-05-061-6/+6
| | | | | | | | | | | | | | | | | | (primarly) MLlib docs While play-testing the Scala and Java code examples in the MLlib docs, I noticed a number of small compile errors, and some typos. This led to finding and fixing a few similar items in other docs. Then in the course of building the site docs to check the result, I found a few small suggestions for the build instructions. I also found a few more formatting and markdown issues uncovered when I accidentally used maruku instead of kramdown. Author: Sean Owen <sowen@cloudera.com> Closes #653 from srowen/SPARK-1727 and squashes the following commits: 6e7c38a [Sean Owen] Final doc updates - one more compile error, and use of mean instead of sum and count 8f5e847 [Sean Owen] Fix markdown syntax issues that maruku flags, even though we use kramdown (but only those that do not affect kramdown's output) 99966a9 [Sean Owen] Update issue tracker URL in docs 23c9ac3 [Sean Owen] Add Scala Naive Bayes example, to use existing example data file (whose format needed a tweak) 8c81982 [Sean Owen] Fix small compile errors and typos across MLlib docs
* [SPARK-1594][MLLIB] Cleaning up MLlib APIs and guideXiangrui Meng2014-05-0534-320/+381
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Final pass before the v1.0 release. * Remove `VectorRDDs` * Move `BinaryClassificationMetrics` from `evaluation.binary` to `evaluation` * Change default value of `addIntercept` to false and allow to add intercept in Ridge and Lasso. * Clean `DecisionTree` package doc and test suite. * Mark model constructors `private[spark]` * Rename `loadLibSVMData` to `loadLibSVMFile` and hide `LabelParser` from users. * Add `saveAsLibSVMFile`. * Add `appendBias` to `MLUtils`. Author: Xiangrui Meng <meng@databricks.com> Closes #524 from mengxr/mllib-cleaning and squashes the following commits: 295dc8b [Xiangrui Meng] update loadLibSVMFile doc 1977ac1 [Xiangrui Meng] fix doc of appendBias 649fcf0 [Xiangrui Meng] rename loadLibSVMData to loadLibSVMFile; hide LabelParser from user APIs 54b812c [Xiangrui Meng] add appendBias a71e7d0 [Xiangrui Meng] add saveAsLibSVMFile d976295 [Xiangrui Meng] Merge branch 'master' into mllib-cleaning b7e5cec [Xiangrui Meng] remove some experimental annotations and make model constructors private[mllib] 9b02b93 [Xiangrui Meng] minor code style update a593ddc [Xiangrui Meng] fix python tests fc28c18 [Xiangrui Meng] mark more classes experimental f6cbbff [Xiangrui Meng] fix Java tests 0af70b0 [Xiangrui Meng] minor 6e139ef [Xiangrui Meng] Merge branch 'master' into mllib-cleaning 94e6dce [Xiangrui Meng] move BinaryLabelCounter and BinaryConfusionMatrixImpl to evaluation.binary df34907 [Xiangrui Meng] clean DecisionTreeSuite to use LocalSparkContext c81807f [Xiangrui Meng] set the default value of AddIntercept to false 03389c0 [Xiangrui Meng] allow to add intercept in Ridge and Lasso c66c56f [Xiangrui Meng] move tree md to package object doc a2695df [Xiangrui Meng] update guide for BinaryClassificationMetrics 9194f4c [Xiangrui Meng] move BinaryClassificationMetrics one level up 1c1a0e3 [Xiangrui Meng] remove VectorRDDs because it only contains one function that is not necessary for us to maintain
* [SPARK-1646] Micro-optimisation of ALSTor Myklebust2014-04-291-5/+17
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This change replaces some Scala `for` and `foreach` constructs with `while` constructs. There may be a slight performance gain on the order of 1-2% when training an ALS model. I trained an ALS model on the Movielens 10M-rating dataset repeatedly both with and without these changes. All 7 runs in both columns were done in a Scala `for` loop like this: for (iter <- 0 to 10) { val before = System.currentTimeMillis() val model = ALS.train(rats, 20, 10) val after = System.currentTimeMillis() println("%d ms".format(after-before)) println("rmse %g".format(computeRmse(model, rats, numRatings))) } The timings were done on a multiuser machine, and I stopped one set of timings after 7 had been completed. It would be nice if somebody with dedicated hardware could confirm my timings. After Before 121980 ms 122041 ms 117069 ms 117127 ms 115332 ms 117523 ms 115381 ms 117402 ms 114635 ms 116550 ms 114140 ms 114076 ms 112993 ms 117200 ms Ratios are about 1.0005, 1.0005, 1.019, 1.0175, 1.01671, 0.99944, and 1.03723. I therefore suspect these changes make for a slight performance gain on the order of 1-2%. Author: Tor Myklebust <tmyklebu@gmail.com> Closes #568 from tmyklebu/alsopt and squashes the following commits: 5ded80f [Tor Myklebust] Fix style. 79595ff [Tor Myklebust] Fix style error. 4ef0313 [Tor Myklebust] Merge branch 'master' of github.com:apache/spark into alsopt 114fb74 [Tor Myklebust] Turn some 'for' loops into 'while' loops. dcf583a [Tor Myklebust] Remove the partitioner member variable; instead, thread that needle everywhere it needs to go. 23d6f91 [Tor Myklebust] Stop making the partitioner configurable. 495784f [Tor Myklebust] Merge branch 'master' of https://github.com/apache/spark 674933a [Tor Myklebust] Fix style. 40edc23 [Tor Myklebust] Fix missing space. f841345 [Tor Myklebust] Fix daft bug creating 'pairs', also for -> foreach. 5ec9e6c [Tor Myklebust] Clean a couple of things up using 'map'. 36a0f43 [Tor Myklebust] Make the partitioner private. d872b09 [Tor Myklebust] Add negative id ALS test. df27697 [Tor Myklebust] Support custom partitioners. Currently we use the same partitioner for users and products. c90b6d8 [Tor Myklebust] Scramble user and product ids before bucketing. c774d7d [Tor Myklebust] Make the partitioner a member variable and use it instead of modding directly.
* [SPARK-1636][MLLIB] Move main methods to examplesXiangrui Meng2014-04-299-304/+7
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | * `NaiveBayes` -> `SparseNaiveBayes` * `KMeans` -> `DenseKMeans` * `SVMWithSGD` and `LogisticRegerssionWithSGD` -> `BinaryClassification` * `ALS` -> `MovieLensALS` * `LinearRegressionWithSGD`, `LassoWithSGD`, and `RidgeRegressionWithSGD` -> `LinearRegression` * `DecisionTree` -> `DecisionTreeRunner` `scopt` is used for parsing command-line parameters. `scopt` has MIT license and it only depends on `scala-library`. Example help message: ~~~ BinaryClassification: an example app for binary classification. Usage: BinaryClassification [options] <input> --numIterations <value> number of iterations --stepSize <value> initial step size, default: 1.0 --algorithm <value> algorithm (SVM,LR), default: LR --regType <value> regularization type (L1,L2), default: L2 --regParam <value> regularization parameter, default: 0.1 <input> input paths to labeled examples in LIBSVM format ~~~ Author: Xiangrui Meng <meng@databricks.com> Closes #584 from mengxr/mllib-main and squashes the following commits: 7b58c60 [Xiangrui Meng] minor 6e35d7e [Xiangrui Meng] make imports explicit and fix code style c6178c9 [Xiangrui Meng] update TS PCA/SVD to use new spark-submit 6acff75 [Xiangrui Meng] use scopt for DecisionTreeRunner be86069 [Xiangrui Meng] use main instead of extending App b3edf68 [Xiangrui Meng] move DecisionTree's main method to examples 8bfaa5a [Xiangrui Meng] change NaiveBayesParams to Params fe23dcb [Xiangrui Meng] remove main from KMeans and add DenseKMeans as an example 67f4448 [Xiangrui Meng] remove main methods from linear regression algorithms and add LinearRegression example b066bbc [Xiangrui Meng] remove main from ALS and add MovieLensALS example b040f3b [Xiangrui Meng] change BinaryClassificationParams to Params 577945b [Xiangrui Meng] remove unused imports from NB 3d299bc [Xiangrui Meng] remove main from LR/SVM and add an example app for binary classification f70878e [Xiangrui Meng] remove main from NaiveBayes and add an example NaiveBayes app 01ec2cd [Xiangrui Meng] Merge branch 'master' into mllib-main 9420692 [Xiangrui Meng] add scopt to examples dependencies
* Improved build configurationwitgo2014-04-281-14/+0
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1, Fix SPARK-1441: compile spark core error with hadoop 0.23.x 2, Fix SPARK-1491: maven hadoop-provided profile fails to build 3, Fix org.scala-lang: * ,org.apache.avro:* inconsistent versions dependency 4, A modified on the sql/catalyst/pom.xml,sql/hive/pom.xml,sql/core/pom.xml (Four spaces formatted into two spaces) Author: witgo <witgo@qq.com> Closes #480 from witgo/format_pom and squashes the following commits: 03f652f [witgo] review commit b452680 [witgo] Merge branch 'master' of https://github.com/apache/spark into format_pom bee920d [witgo] revert fix SPARK-1629: Spark Core missing commons-lang dependence 7382a07 [witgo] Merge branch 'master' of https://github.com/apache/spark into format_pom 6902c91 [witgo] fix SPARK-1629: Spark Core missing commons-lang dependence 0da4bc3 [witgo] merge master d1718ed [witgo] Merge branch 'master' of https://github.com/apache/spark into format_pom e345919 [witgo] add avro dependency to yarn-alpha 77fad08 [witgo] Merge branch 'master' of https://github.com/apache/spark into format_pom 62d0862 [witgo] Fix org.scala-lang: * inconsistent versions dependency 1a162d7 [witgo] Merge branch 'master' of https://github.com/apache/spark into format_pom 934f24d [witgo] review commit cf46edc [witgo] exclude jruby 06e7328 [witgo] Merge branch 'SparkBuild' into format_pom 99464d2 [witgo] fix maven hadoop-provided profile fails to build 0c6c1fc [witgo] Fix compile spark core error with hadoop 0.23.x 6851bec [witgo] Maintain consistent SparkBuild.scala, pom.xml
* [Fix #79] Replace Breakable For Loops By While LoopsSandeep2014-04-231-29/+31
| | | | | | | | | | Author: Sandeep <sandeep@techaddict.me> Closes #503 from techaddict/fix-79 and squashes the following commits: e3f6746 [Sandeep] Style changes 07a4f6b [Sandeep] for loop to While loop 0a6d8e9 [Sandeep] Breakable for loop to While loop
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