| Commit message (Collapse) | Author | Age | Files | Lines |
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This PR refactors / extends the status API introduced in #2696.
- Change StatusAPI from a mixin trait to a class. Before, the new status API methods were directly accessible through SparkContext, whereas now they're accessed through a `sc.statusAPI` field. As long as we were going to add these methods directly to SparkContext, the mixin trait seemed like a good idea, but this might be simpler to reason about and may avoid pitfalls that I've run into while attempting to refactor other parts of SparkContext to use mixins (see #3071, for example).
- Change the name from SparkStatusAPI to SparkStatusTracker.
- Make `getJobIdsForGroup(null)` return ids for jobs that aren't associated with any job group.
- Add `getActiveStageIds()` and `getActiveJobIds()` methods that return the ids of whatever's currently active in this SparkContext. This should simplify davies's progress bar code.
Author: Josh Rosen <joshrosen@databricks.com>
Closes #3197 from JoshRosen/progress-api-improvements and squashes the following commits:
30b0afa [Josh Rosen] Rename SparkStatusAPI to SparkStatusTracker.
d1b08d8 [Josh Rosen] Add missing newlines
2cc7353 [Josh Rosen] Add missing file.
d5eab1f [Josh Rosen] Add getActive[Stage|Job]Ids() methods.
a227984 [Josh Rosen] getJobIdsForGroup(null) should return jobs for default group
c47e294 [Josh Rosen] Remove StatusAPI mixin trait.
(cherry picked from commit 40eb8b6ef3a67e36d0d9492c044981a1da76351d)
Signed-off-by: Reynold Xin <rxin@databricks.com>
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It seems like the winds might have moved away from this approach, but wanted to post the PR anyway because I got it working and to show what it would look like.
Author: Sandy Ryza <sandy@cloudera.com>
Closes #3239 from sryza/sandy-spark-4375 and squashes the following commits:
0ffbe95 [Sandy Ryza] Enable -Dscala-2.11 in sbt
cd42d94 [Sandy Ryza] Update doc
f6644c3 [Sandy Ryza] SPARK-4375 take 2
(cherry picked from commit f5f757e4ed80759dc5668c63d5663651689f8da8)
Signed-off-by: Patrick Wendell <pwendell@gmail.com>
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and Python
The current default regParam is 1.0 and regType is claimed to be none in Python (but actually it is l2), while regParam = 0.0 and regType is L2 in Scala. We should make the default values consistent. This PR sets the default regType to L2 and regParam to 0.01. Note that the default regParam value in LIBLINEAR (and hence scikit-learn) is 1.0. However, we use average loss instead of total loss in our formulation. Hence regParam=1.0 is definitely too heavy.
In LinearRegression, we set regParam=0.0 and regType=None, because we have separate classes for Lasso and Ridge, both of which use regParam=0.01 as the default.
davies atalwalkar
Author: Xiangrui Meng <meng@databricks.com>
Closes #3232 from mengxr/SPARK-4372 and squashes the following commits:
9979837 [Xiangrui Meng] update Ridge/Lasso to use default regParam 0.01 cast input arguments
d3ba096 [Xiangrui Meng] change 'none' back to None
1909a6e [Xiangrui Meng] change default regParam to 0.01 and regType to L2 in LR and SVM
(cherry picked from commit 32218307edc6de2b08d5f7a0db6d566081d27197)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
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This PR adds package "org.apache.spark.ml" with pipeline and parameters, as discussed on the JIRA. This is a joint work of jkbradley etrain shivaram and many others who helped on the design, also with help from marmbrus and liancheng on the Spark SQL side. The design doc can be found at:
https://docs.google.com/document/d/1rVwXRjWKfIb-7PI6b86ipytwbUH7irSNLF1_6dLmh8o/edit?usp=sharing
**org.apache.spark.ml**
This is a new package with new set of ML APIs that address practical machine learning pipelines. (Sorry for taking so long!) It will be an alpha component, so this is definitely not something set in stone. The new set of APIs, inspired by the MLI project from AMPLab and scikit-learn, takes leverage on Spark SQL's schema support and execution plan optimization. It introduces the following components that help build a practical pipeline:
1. Transformer, which transforms a dataset into another
2. Estimator, which fits models to data, where models are transformers
3. Evaluator, which evaluates model output and returns a scalar metric
4. Pipeline, a simple pipeline that consists of transformers and estimators
Parameters could be supplied at fit/transform or embedded with components.
1. Param: a strong-typed parameter key with self-contained doc
2. ParamMap: a param -> value map
3. Params: trait for components with parameters
For any component that implements `Params`, user can easily check the doc by calling `explainParams`:
~~~
> val lr = new LogisticRegression
> lr.explainParams
maxIter: max number of iterations (default: 100)
regParam: regularization constant (default: 0.1)
labelCol: label column name (default: label)
featuresCol: features column name (default: features)
~~~
or user can check individual param:
~~~
> lr.maxIter
maxIter: max number of iterations (default: 100)
~~~
**Please start with the example code in test suites and under `org.apache.spark.examples.ml`, where I put several examples:**
1. run a simple logistic regression job
~~~
val lr = new LogisticRegression()
.setMaxIter(10)
.setRegParam(1.0)
val model = lr.fit(dataset)
model.transform(dataset, model.threshold -> 0.8) // overwrite threshold
.select('label, 'score, 'prediction).collect()
.foreach(println)
~~~
2. run logistic regression with cross-validation and grid search using areaUnderROC (default) as the metric
~~~
val lr = new LogisticRegression
val lrParamMaps = new ParamGridBuilder()
.addGrid(lr.regParam, Array(0.1, 100.0))
.addGrid(lr.maxIter, Array(0, 5))
.build()
val eval = new BinaryClassificationEvaluator
val cv = new CrossValidator()
.setEstimator(lr)
.setEstimatorParamMaps(lrParamMaps)
.setEvaluator(eval)
.setNumFolds(3)
val bestModel = cv.fit(dataset)
~~~
3. run a pipeline that consists of a standard scaler and a logistic regression component
~~~
val scaler = new StandardScaler()
.setInputCol("features")
.setOutputCol("scaledFeatures")
val lr = new LogisticRegression()
.setFeaturesCol(scaler.getOutputCol)
val pipeline = new Pipeline()
.setStages(Array(scaler, lr))
val model = pipeline.fit(dataset)
val predictions = model.transform(dataset)
.select('label, 'score, 'prediction)
.collect()
.foreach(println)
~~~
4. a simple text classification pipeline, which recognizes "spark":
~~~
val training = sparkContext.parallelize(Seq(
LabeledDocument(0L, "a b c d e spark", 1.0),
LabeledDocument(1L, "b d", 0.0),
LabeledDocument(2L, "spark f g h", 1.0),
LabeledDocument(3L, "hadoop mapreduce", 0.0)))
val tokenizer = new Tokenizer()
.setInputCol("text")
.setOutputCol("words")
val hashingTF = new HashingTF()
.setInputCol(tokenizer.getOutputCol)
.setOutputCol("features")
val lr = new LogisticRegression()
.setMaxIter(10)
val pipeline = new Pipeline()
.setStages(Array(tokenizer, hashingTF, lr))
val model = pipeline.fit(training)
val test = sparkContext.parallelize(Seq(
Document(4L, "spark i j k"),
Document(5L, "l m"),
Document(6L, "mapreduce spark"),
Document(7L, "apache hadoop")))
model.transform(test)
.select('id, 'text, 'prediction, 'score)
.collect()
.foreach(println)
~~~
Java examples are very similar. I put example code that creates a simple text classification pipeline in Scala and Java, where a simple tokenizer is defined as a transformer outside `org.apache.spark.ml`.
**What are missing now and will be added soon:**
1. ~~Runtime check of schemas. So before we touch the data, we will go through the schema and make sure column names and types match the input parameters.~~
2. ~~Java examples.~~
3. ~~Store training parameters in trained models.~~
4. (later) Serialization and Python API.
Author: Xiangrui Meng <meng@databricks.com>
Closes #3099 from mengxr/SPARK-3530 and squashes the following commits:
2cc93fd [Xiangrui Meng] hide APIs as much as I can
34319ba [Xiangrui Meng] use local instead local[2] for unit tests
2524251 [Xiangrui Meng] rename PipelineStage.transform to transformSchema
c9daab4 [Xiangrui Meng] remove mockito version
1397ab5 [Xiangrui Meng] use sqlContext from LocalSparkContext instead of TestSQLContext
6ffc389 [Xiangrui Meng] try to fix unit test
a59d8b7 [Xiangrui Meng] doc updates
977fd9d [Xiangrui Meng] add scala ml package object
6d97fe6 [Xiangrui Meng] add AlphaComponent annotation
731f0e4 [Xiangrui Meng] update package doc
0435076 [Xiangrui Meng] remove ;this from setters
fa21d9b [Xiangrui Meng] update extends indentation
f1091b3 [Xiangrui Meng] typo
228a9f4 [Xiangrui Meng] do not persist before calling binary classification metrics
f51cd27 [Xiangrui Meng] rename default to defaultValue
b3be094 [Xiangrui Meng] refactor schema transform in lr
8791e8e [Xiangrui Meng] rename copyValues to inheritValues and make it do the right thing
51f1c06 [Xiangrui Meng] remove leftover code in Transformer
494b632 [Xiangrui Meng] compure score once
ad678e9 [Xiangrui Meng] more doc for Transformer
4306ed4 [Xiangrui Meng] org imports in text pipeline
6e7c1c7 [Xiangrui Meng] update pipeline
4f9e34f [Xiangrui Meng] more doc for pipeline
aa5dbd4 [Xiangrui Meng] fix typo
11be383 [Xiangrui Meng] fix unit tests
3df7952 [Xiangrui Meng] clean up
986593e [Xiangrui Meng] re-org java test suites
2b11211 [Xiangrui Meng] remove external data deps
9fd4933 [Xiangrui Meng] add unit test for pipeline
2a0df46 [Xiangrui Meng] update tests
2d52e4d [Xiangrui Meng] add @AlphaComponent to package-info
27582a4 [Xiangrui Meng] doc changes
73a000b [Xiangrui Meng] add schema transformation layer
6736e87 [Xiangrui Meng] more doc / remove HasMetricName trait
80a8b5e [Xiangrui Meng] rename SimpleTransformer to UnaryTransformer
62ca2bb [Xiangrui Meng] check param parent in set/get
1622349 [Xiangrui Meng] add getModel to PipelineModel
a0e0054 [Xiangrui Meng] update StandardScaler to use SimpleTransformer
d0faa04 [Xiangrui Meng] remove implicit mapping from ParamMap
c7f6921 [Xiangrui Meng] move ParamGridBuilder test to ParamGridBuilderSuite
e246f29 [Xiangrui Meng] re-org:
7772430 [Xiangrui Meng] remove modelParams add a simple text classification pipeline
b95c408 [Xiangrui Meng] remove implicits add unit tests to params
bab3e5b [Xiangrui Meng] update params
fe0ee92 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-3530
6e86d98 [Xiangrui Meng] some code clean-up
2d040b3 [Xiangrui Meng] implement setters inside each class, add Params.copyValues [ci skip]
fd751fc [Xiangrui Meng] add java-friendly versions of fit and tranform
3f810cd [Xiangrui Meng] use multi-model training api in cv
5b8f413 [Xiangrui Meng] rename model to modelParams
9d2d35d [Xiangrui Meng] test varargs and chain model params
f46e927 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-3530
1ef26e0 [Xiangrui Meng] specialize methods/types for Java
df293ed [Xiangrui Meng] switch to setter/getter
376db0a [Xiangrui Meng] pipeline and parameters
(cherry picked from commit 4b736dbab3e177e5265439d37063bb501657d830)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
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Let's give this another go using a version of Hive that shades its JLine dependency.
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Patrick Wendell <pwendell@gmail.com>
Closes #3159 from pwendell/scala-2.11-prashant and squashes the following commits:
e93aa3e [Patrick Wendell] Restoring -Phive-thriftserver profile and cleaning up build script.
f65d17d [Patrick Wendell] Fixing build issue due to merge conflict
a8c41eb [Patrick Wendell] Reverting dev/run-tests back to master state.
7a6eb18 [Patrick Wendell] Merge remote-tracking branch 'apache/master' into scala-2.11-prashant
583aa07 [Prashant Sharma] REVERT ME: removed hive thirftserver
3680e58 [Prashant Sharma] Revert "REVERT ME: Temporarily removing some Cli tests."
935fb47 [Prashant Sharma] Revert "Fixed by disabling a few tests temporarily."
925e90f [Prashant Sharma] Fixed by disabling a few tests temporarily.
2fffed3 [Prashant Sharma] Exclude groovy from sbt build, and also provide a way for such instances in future.
8bd4e40 [Prashant Sharma] Switched to gmaven plus, it fixes random failures observer with its predecessor gmaven.
5272ce5 [Prashant Sharma] SPARK_SCALA_VERSION related bugs.
2121071 [Patrick Wendell] Migrating version detection to PySpark
b1ed44d [Patrick Wendell] REVERT ME: Temporarily removing some Cli tests.
1743a73 [Patrick Wendell] Removing decimal test that doesn't work with Scala 2.11
f5cad4e [Patrick Wendell] Add Scala 2.11 docs
210d7e1 [Patrick Wendell] Revert "Testing new Hive version with shaded jline"
48518ce [Patrick Wendell] Remove association of Hive and Thriftserver profiles.
e9d0a06 [Patrick Wendell] Revert "Enable thritfserver for Scala 2.10 only"
67ec364 [Patrick Wendell] Guard building of thriftserver around Scala 2.10 check
8502c23 [Patrick Wendell] Enable thritfserver for Scala 2.10 only
e22b104 [Patrick Wendell] Small fix in pom file
ec402ab [Patrick Wendell] Various fixes
0be5a9d [Patrick Wendell] Testing new Hive version with shaded jline
4eaec65 [Prashant Sharma] Changed scripts to ignore target.
5167bea [Prashant Sharma] small correction
a4fcac6 [Prashant Sharma] Run against scala 2.11 on jenkins.
80285f4 [Prashant Sharma] MAven equivalent of setting spark.executor.extraClasspath during tests.
034b369 [Prashant Sharma] Setting test jars on executor classpath during tests from sbt.
d4874cb [Prashant Sharma] Fixed Python Runner suite. null check should be first case in scala 2.11.
6f50f13 [Prashant Sharma] Fixed build after rebasing with master. We should use ${scala.binary.version} instead of just 2.10
e56ca9d [Prashant Sharma] Print an error if build for 2.10 and 2.11 is spotted.
937c0b8 [Prashant Sharma] SCALA_VERSION -> SPARK_SCALA_VERSION
cb059b0 [Prashant Sharma] Code review
0476e5e [Prashant Sharma] Scala 2.11 support with repl and all build changes.
(cherry picked from commit daaca14c16dc2c1abc98f15ab8c6f7c14761b627)
Signed-off-by: Patrick Wendell <pwendell@gmail.com>
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Based on SPARK-2434, this PR generates runtime warnings for example implementations (Python, Scala) of PageRank.
Author: Varadharajan Mukundan <srinathsmn@gmail.com>
Closes #2894 from varadharajan/SPARK-4047 and squashes the following commits:
5f9406b [Varadharajan Mukundan] [SPARK-4047] - Point users to LogisticRegressionWithSGD and LogisticRegressionWithLBFGS instead of LogisticRegressionModel
252f595 [Varadharajan Mukundan] a. Generate runtime warnings for
05a018b [Varadharajan Mukundan] Fix PageRank implementation's package reference
5c2bf54 [Varadharajan Mukundan] [SPARK-4047] - Generate runtime warnings for example implementation of PageRank
(cherry picked from commit 974d334cf06a84317234a6c8e2e9ecca8271fa41)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
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pwendell rxin
Please take a look
Author: tedyu <yuzhihong@gmail.com>
Closes #3115 from tedyu/master and squashes the following commits:
2b079c8 [tedyu] SPARK-1297 Upgrade HBase dependency to 0.98
(cherry picked from commit b32734e12d5197bad26c080e529edd875604c6fb)
Signed-off-by: Patrick Wendell <pwendell@gmail.com>
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Here's my attempt to re-port `RecoverableNetworkWordCount` to Java, following the example of its Scala and Java siblings. I fixed a few minor doc/formatting issues along the way I believe.
Author: Sean Owen <sowen@cloudera.com>
Closes #2564 from srowen/SPARK-2548 and squashes the following commits:
0d0bf29 [Sean Owen] Update checkpoint call as in https://github.com/apache/spark/pull/2735
35f23e3 [Sean Owen] Remove old comment about running in standalone mode
179b3c2 [Sean Owen] Re-port RecoverableNetworkWordCount to Java example, and touch up doc / formatting in related examples
(cherry picked from commit 3a02d416cd82a7a942fd6ff4a0e05ff070eb218a)
Signed-off-by: Tathagata Das <tathagata.das1565@gmail.com>
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数组下标越界
Author: xiao321 <1042460381@qq.com>
Closes #3153 from xiao321/patch-1 and squashes the following commits:
0ed17b5 [xiao321] Update JavaCustomReceiver.java
(cherry picked from commit 7c9ec529a3483fab48f728481dd1d3663369e50a)
Signed-off-by: Tathagata Das <tathagata.das1565@gmail.com>
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Changed code so it does not try to serialize Params.
CC: mengxr debasish83 srowen
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #3116 from jkbradley/als-bugfix and squashes the following commits:
e575bd8 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into als-bugfix
9401b16 [Joseph K. Bradley] changed implicitPrefs so it is not serialized to fix MovieLensALS example bug
(cherry picked from commit c315d1316cb2372e90ae3a12f72d5b3304435a6b)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
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### Summary
* Made it easier to construct default Strategy and BoostingStrategy and to set parameters using simple types.
* Added Scala and Java examples for GradientBoostedTrees
* small cleanups and fixes
### Details
GradientBoosting bug fixes (“bug” = bad default options)
* Force boostingStrategy.weakLearnerParams.algo = Regression
* Force boostingStrategy.weakLearnerParams.impurity = impurity.Variance
* Only persist data if not yet persisted (since it causes an error if persisted twice)
BoostingStrategy
* numEstimators: renamed to numIterations
* removed subsamplingRate (duplicated by Strategy)
* removed categoricalFeaturesInfo since it belongs with the weak learner params (since boosting can be oblivious to feature type)
* Changed algo to var (not val) and added BeanProperty, with overload taking String argument
* Added assertValid() method
* Updated defaultParams() method and eliminated defaultWeakLearnerParams() since that belongs in Strategy
Strategy (for DecisionTree)
* Changed algo to var (not val) and added BeanProperty, with overload taking String argument
* Added setCategoricalFeaturesInfo method taking Java Map.
* Cleaned up assertValid
* Changed val’s to def’s since parameters can now be changed.
CC: manishamde mengxr codedeft
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #3094 from jkbradley/gbt-api and squashes the following commits:
7a27e22 [Joseph K. Bradley] scalastyle fix
52013d5 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into gbt-api
e9b8410 [Joseph K. Bradley] Summary of changes
(cherry picked from commit 5b3b6f6f5f029164d7749366506e142b104c1d43)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
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Register MLlib's Vector as a SQL user-defined type (UDT) in both Scala and Python. With this PR, we can easily map a RDD[LabeledPoint] to a SchemaRDD, and then select columns or save to a Parquet file. Examples in Scala/Python are attached. The Scala code was copied from jkbradley.
~~This PR contains the changes from #3068 . I will rebase after #3068 is merged.~~
marmbrus jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes #3070 from mengxr/SPARK-3573 and squashes the following commits:
3a0b6e5 [Xiangrui Meng] organize imports
236f0a0 [Xiangrui Meng] register vector as UDT and provide dataset examples
(cherry picked from commit 1a9c6cddadebdc53d083ac3e0da276ce979b5d1f)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
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...sion trees. jkbradley mengxr chouqin Please review this.
Author: Sung Chung <schung@alpinenow.com>
Closes #2868 from codedeft/SPARK-3161 and squashes the following commits:
5f5a156 [Sung Chung] [SPARK-3161][MLLIB] Adding a node Id caching mechanism for training decision trees.
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Changing the default number of edge partitions to match spark parallelism.
Author: Joseph E. Gonzalez <joseph.e.gonzalez@gmail.com>
Closes #3006 from jegonzal/default_partitions and squashes the following commits:
a9a5c4f [Joseph E. Gonzalez] Changing the default number of edge partitions to match spark parallelism
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This adds a Streaming KMeans algorithm to MLlib. It uses an update rule that generalizes the mini-batch KMeans update to incorporate a decay factor, which allows past data to be forgotten. The decay factor can be specified explicitly, or via a more intuitive "fractional decay" setting, in units of either data points or batches.
The PR includes:
- StreamingKMeans algorithm with decay factor settings
- Usage example
- Additions to documentation clustering page
- Unit tests of basic behavior and decay behaviors
tdas mengxr rezazadeh
Author: freeman <the.freeman.lab@gmail.com>
Author: Jeremy Freeman <the.freeman.lab@gmail.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes #2942 from freeman-lab/streaming-kmeans and squashes the following commits:
b2e5b4a [freeman] Fixes to docs / examples
078617c [Jeremy Freeman] Merge pull request #1 from mengxr/SPARK-3254
2e682c0 [Xiangrui Meng] take discount on previous weights; use BLAS; detect dying clusters
0411bf5 [freeman] Change decay parameterization
9f7aea9 [freeman] Style fixes
374a706 [freeman] Formatting
ad9bdc2 [freeman] Use labeled points and predictOnValues in examples
77dbd3f [freeman] Make initialization check an assertion
9cfc301 [freeman] Make random seed an argument
44050a9 [freeman] Simpler constructor
c7050d5 [freeman] Fix spacing
2899623 [freeman] Use pattern matching for clarity
a4a316b [freeman] Use collect
1472ec5 [freeman] Doc formatting
ea22ec8 [freeman] Fix imports
2086bdc [freeman] Log cluster center updates
ea9877c [freeman] More documentation
9facbe3 [freeman] Bug fix
5db7074 [freeman] Example usage for StreamingKMeans
f33684b [freeman] Add explanation and example to docs
b5b5f8d [freeman] Add better documentation
a0fd790 [freeman] Merge remote-tracking branch 'upstream/master' into streaming-kmeans
9fd9c15 [freeman] Merge remote-tracking branch 'upstream/master' into streaming-kmeans
b93350f [freeman] Streaming KMeans with decay
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Given the popular demand for gradient boosting and AdaBoost in MLlib, I am creating a WIP branch for early feedback on gradient boosting with AdaBoost to follow soon after this PR is accepted. This is based on work done along with hirakendu that was pending due to decision tree optimizations and random forests work.
Ideally, boosting algorithms should work with any base learners. This will soon be possible once the MLlib API is finalized -- we want to ensure we use a consistent interface for the underlying base learners. In the meantime, this PR uses decision trees as base learners for the gradient boosting algorithm. The current PR allows "pluggable" loss functions and provides least squares error and least absolute error by default.
Here is the task list:
- [x] Gradient boosting support
- [x] Pluggable loss functions
- [x] Stochastic gradient boosting support – Re-use the BaggedPoint approach used for RandomForest.
- [x] Binary classification support
- [x] Support configurable checkpointing – This approach will avoid long lineage chains.
- [x] Create classification and regression APIs
- [x] Weighted Ensemble Model -- created a WeightedEnsembleModel class that can be used by ensemble algorithms such as random forests and boosting.
- [x] Unit Tests
Future work:
+ Multi-class classification is currently not supported by this PR since it requires discussion on the best way to support "deviance" as a loss function.
+ BaggedRDD caching -- Avoid repeating feature to bin mapping for each tree estimator after standard API work is completed.
cc: jkbradley hirakendu mengxr etrain atalwalkar chouqin
Author: Manish Amde <manish9ue@gmail.com>
Author: manishamde <manish9ue@gmail.com>
Closes #2607 from manishamde/gbt and squashes the following commits:
991c7b5 [Manish Amde] public api
ff2a796 [Manish Amde] addressing comments
b4c1318 [Manish Amde] removing spaces
8476b6b [Manish Amde] fixing line length
0183cb9 [Manish Amde] fixed naming and formatting issues
1c40c33 [Manish Amde] add newline, removed spaces
e33ab61 [Manish Amde] minor comment
eadbf09 [Manish Amde] parameter renaming
035a2ed [Manish Amde] jkbradley formatting suggestions
9f7359d [Manish Amde] simplified gbt logic and added more tests
49ba107 [Manish Amde] merged from master
eff21fe [Manish Amde] Added gradient boosting tests
3fd0528 [Manish Amde] moved helper methods to new class
a32a5ab [Manish Amde] added test for subsampling without replacement
781542a [Manish Amde] added support for fractional subsampling with replacement
3a18cc1 [Manish Amde] cleaned up api for conversion to bagged point and moved tests to it's own test suite
0e81906 [Manish Amde] improving caching unpersisting logic
d971f73 [Manish Amde] moved RF code to use WeightedEnsembleModel class
fee06d3 [Manish Amde] added weighted ensemble model
1b01943 [Manish Amde] add weights for base learners
9bc6e74 [Manish Amde] adding random seed as parameter
d2c8323 [Manish Amde] Merge branch 'master' into gbt
2ae97b7 [Manish Amde] added documentation for the loss classes
9366b8f [Manish Amde] minor: using numTrees instead of trees.size
3b43896 [Manish Amde] added learning rate for prediction
9b2e35e [Manish Amde] Merge branch 'master' into gbt
6a11c02 [manishamde] fixing formatting
823691b [Manish Amde] fixing RF test
1f47941 [Manish Amde] changing access modifier
5b67102 [Manish Amde] shortened parameter list
5ab3796 [Manish Amde] minor reformatting
9155a9d [Manish Amde] consolidated boosting configuration and added public API
631baea [Manish Amde] Merge branch 'master' into gbt
2cb1258 [Manish Amde] public API support
3b8ffc0 [Manish Amde] added documentation
8e10c63 [Manish Amde] modified unpersist strategy
f62bc48 [Manish Amde] added unpersist
bdca43a [Manish Amde] added timing parameters
2fbc9c7 [Manish Amde] fixing binomial classification prediction
6dd4dd8 [Manish Amde] added support for log loss
9af0231 [Manish Amde] classification attempt
62cc000 [Manish Amde] basic checkpointing
4784091 [Manish Amde] formatting
78ed452 [Manish Amde] added newline and fixed if statement
3973dd1 [Manish Amde] minor indicating subsample is double during comparison
aa8fae7 [Manish Amde] minor refactoring
1a8031c [Manish Amde] sampling with replacement
f1c9ef7 [Manish Amde] Merge branch 'master' into gbt
cdceeef [Manish Amde] added documentation
6251fd5 [Manish Amde] modified method name
5538521 [Manish Amde] disable checkpointing for now
0ae1c0a [Manish Amde] basic gradient boosting code from earlier branches
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This pull request refers to issue: https://issues.apache.org/jira/browse/SPARK-3838
Python example for word2vec
mengxr
Author: Anant <anant.asty@gmail.com>
Closes #2952 from anantasty/SPARK-3838 and squashes the following commits:
87bd723 [Anant] remove stop line
4bd439e [Anant] Changes as per code review. Fized error in word2vec python example, simplified example in docs.
3d3c9ee [Anant] Added empty line after python imports
0c90c31 [Anant] Fixed erroneous code. I was still treating each line to be a single word instead of 16 words
ee4f5f6 [Anant] Fixes from code review comments
c637bcf [Anant] Added word2vec python example to docs
269f31f [Anant] added example in docs
c015b14 [Anant] Added python example for word2vec
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This change replaces usages of colt with commons-math3 equivalents, and makes some minor necessary adjustments to related code and tests to match.
Author: Sean Owen <sowen@cloudera.com>
Closes #2928 from srowen/SPARK-4022 and squashes the following commits:
61a232f [Sean Owen] Fix failure due to different sampling in JavaAPISuite.sample()
16d66b8 [Sean Owen] Simplify seeding with call to reseedRandomGenerator
a1a78e0 [Sean Owen] Use Well19937c
31c7641 [Sean Owen] Fix Python Poisson test by choosing a different seed; about 88% of seeds should work but 1 didn't, it seems
5c9c67f [Sean Owen] Additional test fixes from review
d8f88e0 [Sean Owen] Replace colt with commons-math3. Some tests do not pass yet.
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Author: anant asthana <anant.asty@gmail.com>
Closes #2948 from anantasty/patch-1 and squashes the following commits:
d8fea0b [anant asthana] Just fixing comment that shows usage
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This pull request is a first step towards the implementation of a stable, pull-based progress / status API for Spark (see [SPARK-2321](https://issues.apache.org/jira/browse/SPARK-2321)). For now, I'd like to discuss the basic implementation, API names, and overall interface design. Once we arrive at a good design, I'll go back and add additional methods to expose more information via these API.
#### Design goals:
- Pull-based API
- Usable from Java / Scala / Python (eventually, likely with a wrapper)
- Can be extended to expose more information without introducing binary incompatibilities.
- Returns immutable objects.
- Don't leak any implementation details, preserving our freedom to change the implementation.
#### Implementation:
- Add public methods (`getJobInfo`, `getStageInfo`) to SparkContext to allow status / progress information to be retrieved.
- Add public interfaces (`SparkJobInfo`, `SparkStageInfo`) for our API return values. These interfaces consist entirely of Java-style getter methods. The interfaces are currently implemented in Java. I decided to explicitly separate the interface from its implementation (`SparkJobInfoImpl`, `SparkStageInfoImpl`) in order to prevent users from constructing these responses themselves.
-Allow an existing JobProgressListener to be used when constructing a live SparkUI. This allows us to re-use this listeners in the implementation of this status API. There are a few reasons why this listener re-use makes sense:
- The status API and web UI are guaranteed to show consistent information.
- These listeners are already well-tested.
- The same garbage-collection / information retention configurations can apply to both this API and the web UI.
- Extend JobProgressListener to maintain `jobId -> Job` and `stageId -> Stage` mappings.
The progress API methods are implemented in a separate trait that's mixed into SparkContext. This helps to avoid SparkContext.scala from becoming larger and more difficult to read.
Author: Josh Rosen <joshrosen@databricks.com>
Author: Josh Rosen <joshrosen@apache.org>
Closes #2696 from JoshRosen/progress-reporting-api and squashes the following commits:
e6aa78d [Josh Rosen] Add tests.
b585c16 [Josh Rosen] Accept SparkListenerBus instead of more specific subclasses.
c96402d [Josh Rosen] Address review comments.
2707f98 [Josh Rosen] Expose current stage attempt id
c28ba76 [Josh Rosen] Update demo code:
646ff1d [Josh Rosen] Document spark.ui.retainedJobs.
7f47d6d [Josh Rosen] Clean up SparkUI constructors, per Andrew's feedback.
b77b3d8 [Josh Rosen] Merge remote-tracking branch 'origin/master' into progress-reporting-api
787444c [Josh Rosen] Move status API methods into trait that can be mixed into SparkContext.
f9a9a00 [Josh Rosen] More review comments:
3dc79af [Josh Rosen] Remove creation of unused listeners in SparkContext.
249ca16 [Josh Rosen] Address several review comments:
da5648e [Josh Rosen] Add example of basic progress reporting in Java.
7319ffd [Josh Rosen] Add getJobIdsForGroup() and num*Tasks() methods.
cc568e5 [Josh Rosen] Add note explaining that interfaces should not be implemented outside of Spark.
6e840d4 [Josh Rosen] Remove getter-style names and "consistent snapshot" semantics:
08cbec9 [Josh Rosen] Begin to sketch the interfaces for a stable, public status API.
ac2d13a [Josh Rosen] Add jobId->stage, stageId->stage mappings in JobProgressListener
24de263 [Josh Rosen] Create UI listeners in SparkContext instead of in Tabs:
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Now graphx.SynthBenchmark example has an option of iteration number named as "niter". However, in its document, it is named as "niters". The mismatch between the implementation and document causes certain IllegalArgumentException while trying that example.
Author: Grace <jie.huang@intel.com>
Closes #2888 from GraceH/synthbenchmark and squashes the following commits:
f101ee1 [Grace] Modify option name according to example doc
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Thare are some inconsistent spellings 'MLlib' and 'MLLib' in some documents and source codes.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes #2903 from sarutak/SPARK-4055 and squashes the following commits:
b031640 [Kousuke Saruta] Fixed inconsistent spelling "MLlib and MLLib"
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Changed the usage string to correctly reflect the file name.
Author: Karthik <karthik.gomadam@gmail.com>
Closes #2699 from namelessnerd/patch-1 and squashes the following commits:
8570e33 [Karthik] Update JavaCustomReceiver.java
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Author: Sandy Ryza <sandy@cloudera.com>
Closes #789 from sryza/sandy-spark-1813 and squashes the following commits:
48b05e9 [Sandy Ryza] Simplify
b824932 [Sandy Ryza] Allow both spark.kryo.classesToRegister and spark.kryo.registrator at the same time
6a15bb7 [Sandy Ryza] Small fix
a2278c0 [Sandy Ryza] Respond to review comments
6ef592e [Sandy Ryza] SPARK-1813. Add a utility to SparkConf that makes using Kryo really easy
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Programming Guide
Having Python examples in Streaming Programming Guide.
Also add RecoverableNetworkWordCount example.
Author: Davies Liu <davies.liu@gmail.com>
Author: Davies Liu <davies@databricks.com>
Closes #2808 from davies/pyguide and squashes the following commits:
8d4bec4 [Davies Liu] update readme
26a7e37 [Davies Liu] fix format
3821c4d [Davies Liu] address comments, add missing file
7e4bb8a [Davies Liu] add Python examples in Streaming Programming Guide
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SPARK-3934: When run with a mix of unordered categorical and continuous features, on multiclass classification, RandomForest fails. The bug is in the sanity checks in getFeatureOffset and getLeftRightFeatureOffsets, which use the wrong indices for checking whether features are unordered.
Fix: Remove the sanity checks since they are not really needed, and since they would require DTStatsAggregator to keep track of an extra set of indices (for the feature subset).
Added test to RandomForestSuite which failed with old version but now works.
SPARK-3918: Added baggedInput.unpersist at end of training.
Also:
* I removed DTStatsAggregator.isUnordered since it is no longer used.
* DecisionTreeMetadata: Added logWarning when maxBins is automatically reduced.
* Updated DecisionTreeRunner to explicitly fix the test data to have the same number of features as the training data. This is a temporary fix which should eventually be replaced by pre-indexing both datasets.
* RandomForestModel: Updated toString to print total number of nodes in forest.
* Changed Predict class to be public DeveloperApi. This was necessary to allow users to create their own trees by hand (for testing).
CC: mengxr manishamde chouqin codedeft Just notifying you of these small bug fixes.
Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>
Closes #2785 from jkbradley/dtrunner-update and squashes the following commits:
9132321 [Joseph K. Bradley] merged with master, fixed imports
9dbd000 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update
e116473 [Joseph K. Bradley] Changed Predict class to be public DeveloperApi.
f502e65 [Joseph K. Bradley] bug fix for SPARK-3934
7f3d60f [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update
ba567ab [Joseph K. Bradley] Changed DTRunner to load test data using same number of features as in training data.
4e88c1f [Joseph K. Bradley] changed RF toString to print total number of nodes
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Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes #2834 from adrian-wang/sqlpypath and squashes the following commits:
da7aa95 [Daoyuan Wang] fix file path using path.join
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Author: Kun Li <jacky.likun@gmail.com>
Closes #2809 from jackylk/patch-1 and squashes the following commits:
46c926b [Kun Li] typo in HiveFromSpark
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Previously, when the val partitionStrategy was created it called a function in the Analytics object which was a copy of the PartitionStrategy.fromString() method. This function has been removed, and the assignment of partitionStrategy now uses the PartitionStrategy.fromString method instead. In this way, it better matches the declarations of edge/vertex StorageLevel variables.
Author: NamelessAnalyst <NamelessAnalyst@users.noreply.github.com>
Closes #2569 from NamelessAnalyst/branch-1.1 and squashes the following commits:
c24ff51 [NamelessAnalyst] Update Analytics.scala
(cherry picked from commit 5a21e3e7e97f135c81c664098a723434b910f09d)
Signed-off-by: Ankur Dave <ankurdave@gmail.com>
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This patch brings Python API for Streaming.
This patch is based on work from @giwa
Author: giwa <ugw.gi.world@gmail.com>
Author: Ken Takagiwa <ken@Kens-MacBook-Pro.local>
Author: Davies Liu <davies.liu@gmail.com>
Author: Ken Takagiwa <ken@kens-mbp.gateway.sonic.net>
Author: Tathagata Das <tathagata.das1565@gmail.com>
Author: Ken <ugw.gi.world@gmail.com>
Author: Ken Takagiwa <ugw.gi.world@gmail.com>
Author: Matthew Farrellee <matt@redhat.com>
Closes #2538 from davies/streaming and squashes the following commits:
64561e4 [Davies Liu] fix tests
331ecce [Davies Liu] fix example
3e2492b [Davies Liu] change updateStateByKey() to easy API
182be73 [Davies Liu] Merge branch 'master' of github.com:apache/spark into streaming
02d0575 [Davies Liu] add wrapper for foreachRDD()
bebeb4a [Davies Liu] address all comments
6db00da [Davies Liu] Merge branch 'master' of github.com:apache/spark into streaming
8380064 [Davies Liu] Merge branch 'master' of github.com:apache/spark into streaming
52c535b [Davies Liu] remove fix for sum()
e108ec1 [Davies Liu] address comments
37fe06f [Davies Liu] use random port for callback server
d05871e [Davies Liu] remove reuse of PythonRDD
be5e5ff [Davies Liu] merge branch of env, make tests stable.
8071541 [Davies Liu] Merge branch 'env' into streaming
c7bbbce [Davies Liu] fix sphinx docs
6bb9d91 [Davies Liu] Merge branch 'master' of github.com:apache/spark into streaming
4d0ea8b [Davies Liu] clear reference of SparkEnv after stop
54bd92b [Davies Liu] improve tests
c2b31cb [Davies Liu] Merge branch 'master' of github.com:apache/spark into streaming
7a88f9f [Davies Liu] rollback RDD.setContext(), use textFileStream() to test checkpointing
bd8a4c2 [Davies Liu] fix scala style
7797c70 [Davies Liu] refactor
ff88bec [Davies Liu] rename RDDFunction to TransformFunction
d328aca [Davies Liu] fix serializer in queueStream
6f0da2f [Davies Liu] recover from checkpoint
fa7261b [Davies Liu] refactor
a13ff34 [Davies Liu] address comments
8466916 [Davies Liu] support checkpoint
9a16bd1 [Davies Liu] change number of partitions during tests
b98d63f [Davies Liu] change private[spark] to private[python]
eed6e2a [Davies Liu] rollback not needed changes
e00136b [Davies Liu] address comments
069a94c [Davies Liu] fix the number of partitions during window()
338580a [Davies Liu] change _first(), _take(), _collect() as private API
19797f9 [Davies Liu] clean up
6ebceca [Davies Liu] add more tests
c40c52d [Davies Liu] change first(), take(n) to has the same behavior as RDD
98ac6c2 [Davies Liu] support ssc.transform()
b983f0f [Davies Liu] address comments
847f9b9 [Davies Liu] add more docs, add first(), take()
e059ca2 [Davies Liu] move check of window into Python
fce0ef5 [Davies Liu] rafactor of foreachRDD()
7001b51 [Davies Liu] refactor of queueStream()
26ea396 [Davies Liu] refactor
74df565 [Davies Liu] fix print and docs
b32774c [Davies Liu] move java_import into streaming
604323f [Davies Liu] enable streaming tests
c499ba0 [Davies Liu] remove Time and Duration
3f0fb4b [Davies Liu] refactor fix tests
c28f520 [Davies Liu] support updateStateByKey
d357b70 [Davies Liu] support windowed dstream
bd13026 [Davies Liu] fix examples
eec401e [Davies Liu] refactor, combine TransformedRDD, fix reuse PythonRDD, fix union
9a57685 [Davies Liu] fix python style
bd27874 [Davies Liu] fix scala style
7339be0 [Davies Liu] delete tests
7f53086 [Davies Liu] support transform(), refactor and cleanup
df098fc [Davies Liu] Merge branch 'master' into giwa
550dfd9 [giwa] WIP fixing 1.1 merge
5cdb6fa [giwa] changed for SCCallSiteSync
e685853 [giwa] meged with rebased 1.1 branch
2d32a74 [giwa] added some StreamingContextTestSuite
4a59e1e [giwa] WIP:added more test for StreamingContext
8ffdbf1 [giwa] added atexit to handle callback server
d5f5fcb [giwa] added comment for StreamingContext.sparkContext
63c881a [giwa] added StreamingContext.sparkContext
d39f102 [giwa] added StreamingContext.remember
d542743 [giwa] clean up code
2fdf0de [Matthew Farrellee] Fix scalastyle errors
c0a06bc [giwa] delete not implemented functions
f385976 [giwa] delete inproper comments
b0f2015 [giwa] added comment in dstream._test_output
bebb3f3 [giwa] remove the last brank line
fbed8da [giwa] revert pom.xml
8ed93af [giwa] fixed explanaiton
066ba90 [giwa] revert pom.xml
fa4af88 [giwa] remove duplicated import
6ae3caa [giwa] revert pom.xml
7dc7391 [giwa] fixed typo
62dc7a3 [giwa] clean up exmples
f04882c [giwa] clen up examples
b171ec3 [giwa] fixed pep8 violation
f198d14 [giwa] clean up code
3166d31 [giwa] clean up
c00e091 [giwa] change test case not to use awaitTermination
e80647e [giwa] adopted the latest compression way of python command
58e41ff [giwa] merge with master
455e5af [giwa] removed wasted print in DStream
af336b7 [giwa] add comments
ddd4ee1 [giwa] added TODO coments
99ce042 [giwa] added saveAsTextFiles and saveAsPickledFiles
2a06cdb [giwa] remove waste duplicated code
c5ecfc1 [giwa] basic function test cases are passed
8dcda84 [giwa] all tests are passed if numSlice is 2 and the numver of each input is over 4
795b2cd [giwa] broke something
1e126bf [giwa] WIP: solved partitioned and None is not recognized
f67cf57 [giwa] added mapValues and flatMapVaules WIP for glom and mapPartitions test
953deb0 [giwa] edited the comment to add more precise description
af610d3 [giwa] removed unnesessary changes
c1d546e [giwa] fixed PEP-008 violation
99410be [giwa] delete waste file
b3b0362 [giwa] added basic operation test cases
9cde7c9 [giwa] WIP added test case
bd3ba53 [giwa] WIP
5c04a5f [giwa] WIP: added PythonTestInputStream
019ef38 [giwa] WIP
1934726 [giwa] update comment
376e3ac [giwa] WIP
932372a [giwa] clean up dstream.py
0b09cff [giwa] added stop in StreamingContext
92e333e [giwa] implemented reduce and count function in Dstream
1b83354 [giwa] Removed the waste line
88f7506 [Ken Takagiwa] Kill py4j callback server properly
54b5358 [Ken Takagiwa] tried to restart callback server
4f07163 [Tathagata Das] Implemented DStream.foreachRDD in the Python API using Py4J callback server.
fe02547 [Ken Takagiwa] remove waste file
2ad7bd3 [Ken Takagiwa] clean up codes
6197a11 [Ken Takagiwa] clean up code
eb4bf48 [Ken Takagiwa] fix map function
98c2a00 [Ken Takagiwa] added count operation but this implementation need double check
58591d2 [Ken Takagiwa] reduceByKey is working
0df7111 [Ken Takagiwa] delete old file
f485b1d [Ken Takagiwa] fied input of socketTextDStream
dd6de81 [Ken Takagiwa] initial commit for socketTextStream
247fd74 [Ken Takagiwa] modified the code base on comment in https://github.com/tdas/spark/pull/10
4bcb318 [Ken Takagiwa] implementing transform function in Python
38adf95 [Ken Takagiwa] added reducedByKey not working yet
66fcfff [Ken Takagiwa] modify dstream.py to fix indent error
41886c2 [Ken Takagiwa] comment PythonDStream.PairwiseDStream
0b99bec [Ken] initial commit for pySparkStreaming
c214199 [giwa] added testcase for combineByKey
5625bdc [giwa] added gorupByKey testcase
10ab87b [giwa] added sparkContext as input parameter in StreamingContext
10b5b04 [giwa] removed wasted print in DStream
e54f986 [giwa] add comments
16aa64f [giwa] added TODO coments
74535d4 [giwa] added saveAsTextFiles and saveAsPickledFiles
f76c182 [giwa] remove waste duplicated code
18c8723 [giwa] modified streaming test case to add coment
13fb44c [giwa] basic function test cases are passed
3000b2b [giwa] all tests are passed if numSlice is 2 and the numver of each input is over 4
ff14070 [giwa] broke something
bcdec33 [giwa] WIP: solved partitioned and None is not recognized
270a9e1 [giwa] added mapValues and flatMapVaules WIP for glom and mapPartitions test
bb10956 [giwa] edited the comment to add more precise description
253a863 [giwa] removed unnesessary changes
3d37822 [giwa] fixed PEP-008 violation
f21cab3 [giwa] delete waste file
878bad7 [giwa] added basic operation test cases
ce2acd2 [giwa] WIP added test case
9ad6855 [giwa] WIP
1df77f5 [giwa] WIP: added PythonTestInputStream
1523b66 [giwa] WIP
8a0fbbc [giwa] update comment
fe648e3 [giwa] WIP
29c2bc5 [giwa] initial commit for testcase
4d40d63 [giwa] clean up dstream.py
c462bb3 [giwa] added stop in StreamingContext
d2c01ba [giwa] clean up examples
3c45cd2 [giwa] implemented reduce and count function in Dstream
b349649 [giwa] Removed the waste line
3b498e1 [Ken Takagiwa] Kill py4j callback server properly
84a9668 [Ken Takagiwa] tried to restart callback server
9ab8952 [Tathagata Das] Added extra line.
05e991b [Tathagata Das] Added missing file
b1d2a30 [Tathagata Das] Implemented DStream.foreachRDD in the Python API using Py4J callback server.
678e854 [Ken Takagiwa] remove waste file
0a8bbbb [Ken Takagiwa] clean up codes
bab31c1 [Ken Takagiwa] clean up code
72b9738 [Ken Takagiwa] fix map function
d3ee86a [Ken Takagiwa] added count operation but this implementation need double check
15feea9 [Ken Takagiwa] edit python sparkstreaming example
6f98e50 [Ken Takagiwa] reduceByKey is working
c455c8d [Ken Takagiwa] added reducedByKey not working yet
dc6995d [Ken Takagiwa] delete old file
b31446a [Ken Takagiwa] fixed typo of network_workdcount.py
ccfd214 [Ken Takagiwa] added doctest for pyspark.streaming.duration
0d1b954 [Ken Takagiwa] fied input of socketTextDStream
f746109 [Ken Takagiwa] initial commit for socketTextStream
bb7ccf3 [Ken Takagiwa] remove unused import in python
224fc5e [Ken Takagiwa] add empty line
d2099d8 [Ken Takagiwa] sorted the import following Spark coding convention
5bac7ec [Ken Takagiwa] revert streaming/pom.xml
e1df940 [Ken Takagiwa] revert pom.xml
494cae5 [Ken Takagiwa] remove not implemented DStream functions in python
17a74c6 [Ken Takagiwa] modified the code base on comment in https://github.com/tdas/spark/pull/10
1a0f065 [Ken Takagiwa] implementing transform function in Python
d7b4d6f [Ken Takagiwa] added reducedByKey not working yet
87438e2 [Ken Takagiwa] modify dstream.py to fix indent error
b406252 [Ken Takagiwa] comment PythonDStream.PairwiseDStream
454981d [Ken] initial commit for pySparkStreaming
150b94c [giwa] added some StreamingContextTestSuite
f7bc8f9 [giwa] WIP:added more test for StreamingContext
ee50c5a [giwa] added atexit to handle callback server
fdc9125 [giwa] added comment for StreamingContext.sparkContext
f5bfb70 [giwa] added StreamingContext.sparkContext
da09768 [giwa] added StreamingContext.remember
d68b568 [giwa] clean up code
4afa390 [giwa] clean up code
1fd6bc7 [Ken Takagiwa] Merge pull request #2 from mattf/giwa-master
d9d59fe [Matthew Farrellee] Fix scalastyle errors
67473a9 [giwa] delete not implemented functions
c97377c [giwa] delete inproper comments
2ea769e [giwa] added comment in dstream._test_output
3b27bd4 [giwa] remove the last brank line
acfcaeb [giwa] revert pom.xml
93f7637 [giwa] fixed explanaiton
50fd6f9 [giwa] revert pom.xml
4f82c89 [giwa] remove duplicated import
9d1de23 [giwa] revert pom.xml
7339df2 [giwa] fixed typo
9c85e48 [giwa] clean up exmples
24f95db [giwa] clen up examples
0d30109 [giwa] fixed pep8 violation
b7dab85 [giwa] improve test case
583e66d [giwa] move tests for streaming inside streaming directory
1d84142 [giwa] remove unimplement test
f0ea311 [giwa] clean up code
171edeb [giwa] clean up
4dedd2d [giwa] change test case not to use awaitTermination
268a6a5 [giwa] Changed awaitTermination not to call awaitTermincation in Scala. Just use time.sleep instread
09a28bf [giwa] improve testcases
58150f5 [giwa] Changed the test case to focus the test operation
199e37f [giwa] adopted the latest compression way of python command
185fdbf [giwa] merge with master
f1798c4 [giwa] merge with master
e70f706 [giwa] added testcase for combineByKey
e162822 [giwa] added gorupByKey testcase
97742fe [giwa] added sparkContext as input parameter in StreamingContext
14d4c0e [giwa] removed wasted print in DStream
6d8190a [giwa] add comments
4aa99e4 [giwa] added TODO coments
e9fab72 [giwa] added saveAsTextFiles and saveAsPickledFiles
94f2b65 [giwa] remove waste duplicated code
580fbc2 [giwa] modified streaming test case to add coment
99e4bb3 [giwa] basic function test cases are passed
7051a84 [giwa] all tests are passed if numSlice is 2 and the numver of each input is over 4
35933e1 [giwa] broke something
9767712 [giwa] WIP: solved partitioned and None is not recognized
4f2d7e6 [giwa] added mapValues and flatMapVaules WIP for glom and mapPartitions test
33c0f94d [giwa] edited the comment to add more precise description
774f18d [giwa] removed unnesessary changes
3a671cc [giwa] remove export PYSPARK_PYTHON in spark submit
8efa266 [giwa] fixed PEP-008 violation
fa75d71 [giwa] delete waste file
7f96294 [giwa] added basic operation test cases
3dda31a [giwa] WIP added test case
1f68b78 [giwa] WIP
c05922c [giwa] WIP: added PythonTestInputStream
1fd12ae [giwa] WIP
c880a33 [giwa] update comment
5d22c92 [giwa] WIP
ea4b06b [giwa] initial commit for testcase
5a9b525 [giwa] clean up dstream.py
79c5809 [giwa] added stop in StreamingContext
189dcea [giwa] clean up examples
b8d7d24 [giwa] implemented reduce and count function in Dstream
b6468e6 [giwa] Removed the waste line
b47b5fd [Ken Takagiwa] Kill py4j callback server properly
19ddcdd [Ken Takagiwa] tried to restart callback server
c9fc124 [Tathagata Das] Added extra line.
4caae3f [Tathagata Das] Added missing file
4eff053 [Tathagata Das] Implemented DStream.foreachRDD in the Python API using Py4J callback server.
5e822d4 [Ken Takagiwa] remove waste file
aeaf8a5 [Ken Takagiwa] clean up codes
9fa249b [Ken Takagiwa] clean up code
05459c6 [Ken Takagiwa] fix map function
a9f4ecb [Ken Takagiwa] added count operation but this implementation need double check
d1ee6ca [Ken Takagiwa] edit python sparkstreaming example
0b8b7d0 [Ken Takagiwa] reduceByKey is working
d25d5cf [Ken Takagiwa] added reducedByKey not working yet
7f7c5d1 [Ken Takagiwa] delete old file
967dc26 [Ken Takagiwa] fixed typo of network_workdcount.py
57fb740 [Ken Takagiwa] added doctest for pyspark.streaming.duration
4b69fb1 [Ken Takagiwa] fied input of socketTextDStream
02f618a [Ken Takagiwa] initial commit for socketTextStream
4ce4058 [Ken Takagiwa] remove unused import in python
856d98e [Ken Takagiwa] add empty line
490e338 [Ken Takagiwa] sorted the import following Spark coding convention
5594bd4 [Ken Takagiwa] revert pom.xml
2adca84 [Ken Takagiwa] remove not implemented DStream functions in python
e551e13 [Ken Takagiwa] add coment for hack why PYSPARK_PYTHON is needed in spark-submit
3758175 [Ken Takagiwa] add coment for hack why PYSPARK_PYTHON is needed in spark-submit
c5518b4 [Ken Takagiwa] modified the code base on comment in https://github.com/tdas/spark/pull/10
dcf243f [Ken Takagiwa] implementing transform function in Python
9af03f4 [Ken Takagiwa] added reducedByKey not working yet
6e0d9c7 [Ken Takagiwa] modify dstream.py to fix indent error
e497b9b [Ken Takagiwa] comment PythonDStream.PairwiseDStream
5c3a683 [Ken] initial commit for pySparkStreaming
665bfdb [giwa] added testcase for combineByKey
a3d2379 [giwa] added gorupByKey testcase
636090a [giwa] added sparkContext as input parameter in StreamingContext
e7ebb08 [giwa] removed wasted print in DStream
d8b593b [giwa] add comments
ea9c873 [giwa] added TODO coments
89ae38a [giwa] added saveAsTextFiles and saveAsPickledFiles
e3033fc [giwa] remove waste duplicated code
a14c7e1 [giwa] modified streaming test case to add coment
536def4 [giwa] basic function test cases are passed
2112638 [giwa] all tests are passed if numSlice is 2 and the numver of each input is over 4
080541a [giwa] broke something
0704b86 [giwa] WIP: solved partitioned and None is not recognized
90a6484 [giwa] added mapValues and flatMapVaules WIP for glom and mapPartitions test
a65f302 [giwa] edited the comment to add more precise description
bdde697 [giwa] removed unnesessary changes
e8c7bfc [giwa] remove export PYSPARK_PYTHON in spark submit
3334169 [giwa] fixed PEP-008 violation
db0a303 [giwa] delete waste file
2cfd3a0 [giwa] added basic operation test cases
90ae568 [giwa] WIP added test case
a120d07 [giwa] WIP
f671cdb [giwa] WIP: added PythonTestInputStream
56fae45 [giwa] WIP
e35e101 [giwa] Merge branch 'master' into testcase
ba5112d [giwa] update comment
28aa56d [giwa] WIP
fb08559 [giwa] initial commit for testcase
a613b85 [giwa] clean up dstream.py
c40c0ef [giwa] added stop in StreamingContext
31e4260 [giwa] clean up examples
d2127d6 [giwa] implemented reduce and count function in Dstream
48f7746 [giwa] Removed the waste line
0f83eaa [Ken Takagiwa] delete py4j 0.8.1
1679808 [Ken Takagiwa] Kill py4j callback server properly
f96cd4e [Ken Takagiwa] tried to restart callback server
fe86198 [Ken Takagiwa] add py4j 0.8.2.1 but server is not launched
1064fe0 [Ken Takagiwa] Merge branch 'master' of https://github.com/giwa/spark
28c6620 [Ken Takagiwa] Implemented DStream.foreachRDD in the Python API using Py4J callback server
85b0fe1 [Ken Takagiwa] Merge pull request #1 from tdas/python-foreach
54e2e8c [Tathagata Das] Added extra line.
e185338 [Tathagata Das] Added missing file
a778d4b [Tathagata Das] Implemented DStream.foreachRDD in the Python API using Py4J callback server.
cc2092b [Ken Takagiwa] remove waste file
d042ac6 [Ken Takagiwa] clean up codes
84a021f [Ken Takagiwa] clean up code
bd20e17 [Ken Takagiwa] fix map function
d01a125 [Ken Takagiwa] added count operation but this implementation need double check
7d05109 [Ken Takagiwa] merge with remote branch
ae464e0 [Ken Takagiwa] edit python sparkstreaming example
04af046 [Ken Takagiwa] reduceByKey is working
3b6d7b0 [Ken Takagiwa] implementing transform function in Python
571d52d [Ken Takagiwa] added reducedByKey not working yet
5720979 [Ken Takagiwa] delete old file
e604fcb [Ken Takagiwa] fixed typo of network_workdcount.py
4b7c08b [Ken Takagiwa] Merge branch 'master' of https://github.com/giwa/spark
ce7d426 [Ken Takagiwa] added doctest for pyspark.streaming.duration
a8c9fd5 [Ken Takagiwa] fixed for socketTextStream
a61fa9e [Ken Takagiwa] fied input of socketTextDStream
1e84f41 [Ken Takagiwa] initial commit for socketTextStream
6d012f7 [Ken Takagiwa] remove unused import in python
25d30d5 [Ken Takagiwa] add empty line
6e0a64a [Ken Takagiwa] sorted the import following Spark coding convention
fa4a7fc [Ken Takagiwa] revert streaming/pom.xml
8f8202b [Ken Takagiwa] revert streaming pom.xml
c9d79dd [Ken Takagiwa] revert pom.xml
57e3e52 [Ken Takagiwa] remove not implemented DStream functions in python
0a516f5 [Ken Takagiwa] add coment for hack why PYSPARK_PYTHON is needed in spark-submit
a7a0b5c [Ken Takagiwa] add coment for hack why PYSPARK_PYTHON is needed in spark-submit
72bfc66 [Ken Takagiwa] modified the code base on comment in https://github.com/tdas/spark/pull/10
69e9cd3 [Ken Takagiwa] implementing transform function in Python
94a0787 [Ken Takagiwa] added reducedByKey not working yet
88068cf [Ken Takagiwa] modify dstream.py to fix indent error
1367be5 [Ken Takagiwa] comment PythonDStream.PairwiseDStream
eb2b3ba [Ken] Merge remote-tracking branch 'upstream/master'
d8e51f9 [Ken] initial commit for pySparkStreaming
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Provide a parent class for the Params case classes used in many MLlib examples, where the parent class pretty-prints the case class fields:
Param1Name Param1Value
Param2Name Param2Value
...
Using this class will make it easier to print test settings to logs.
Also, updated DecisionTreeRunner to print a little more info.
CC: mengxr
Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>
Closes #2700 from jkbradley/dtrunner-update and squashes the following commits:
cff873f [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update
7a08ae4 [Joseph K. Bradley] code review comment updates
b4d2043 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update
d8228a7 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update
0fc9c64 [Joseph K. Bradley] Added abstract TestParams class for mllib example parameters
12b7798 [Joseph K. Bradley] Added abstract class TestParams for pretty-printing Params values
5f84f03 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update
f7441b6 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update
19eb6fc [Joseph K. Bradley] Updated DecisionTreeRunner to print training time.
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Provide example for `RowMatrix.columnSimilarity()`
Author: Reza Zadeh <rizlar@gmail.com>
Closes #2622 from rezazadeh/dimsumexample and squashes the following commits:
8f20b82 [Reza Zadeh] update comment
379066d [Reza Zadeh] cache rows
792b81c [Reza Zadeh] Address review comments
e573c7a [Reza Zadeh] Average absolute error
b15685f [Reza Zadeh] Use scopt. Distribute evaluation.
eca3dfd [Reza Zadeh] Documentation
ac96fb2 [Reza Zadeh] Compute approximation error, add command line.
4533579 [Reza Zadeh] CosineSimilarity Example
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This patch forces use of commons http client 4.2 in Kinesis-asl profile so that the AWS SDK does not run into dependency conflicts
Author: aniketbhatnagar <aniket.bhatnagar@gmail.com>
Closes #2535 from aniketbhatnagar/Kinesis-HttpClient-Dep-Fix and squashes the following commits:
aa2079f [aniketbhatnagar] Merge branch 'Kinesis-HttpClient-Dep-Fix' of https://github.com/aniketbhatnagar/spark into Kinesis-HttpClient-Dep-Fix
73f55f6 [aniketbhatnagar] SPARK-3638 | Forced a compatible version of http client in kinesis-asl profile
70cc75b [aniketbhatnagar] deleted merge files
725dbc9 [aniketbhatnagar] Merge remote-tracking branch 'origin/Kinesis-HttpClient-Dep-Fix' into Kinesis-HttpClient-Dep-Fix
4ed61d8 [aniketbhatnagar] SPARK-3638 | Forced a compatible version of http client in kinesis-asl profile
9cd6103 [aniketbhatnagar] SPARK-3638 | Forced a compatible version of http client in kinesis-asl profile
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SQL example code for Python, as shown on [SQL Programming Guide](https://spark.apache.org/docs/1.0.2/sql-programming-guide.html)
Author: jyotiska <jyotiska123@gmail.com>
Closes #2521 from jyotiska/sql_example and squashes the following commits:
1471dcb [jyotiska] added imports for sql
b25e436 [jyotiska] pep 8 compliance
43fd10a [jyotiska] lines broken to maintain 80 char limit
b4fdf4e [jyotiska] removed blank lines
83d5ab7 [jyotiska] added inferschema and applyschema to the demo
306667e [jyotiska] replaced blank line with end line
c90502a [jyotiska] fixed new line
4939a70 [jyotiska] added new line at end for python style
0b46148 [jyotiska] fixed appname for python sql example
8f67b5b [jyotiska] added python sql example
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topicpMap to topicMap
Author: Gaspar Munoz <munozs.88@gmail.com>
Closes #2614 from gasparms/patch-1 and squashes the following commits:
00aab2c [Gaspar Munoz] Typo error in KafkaWordCount example
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Call SparkContext.stop() in all examples (and touch up minor nearby code style issues while at it)
Author: Sean Owen <sowen@cloudera.com>
Closes #2575 from srowen/SPARK-2626 and squashes the following commits:
5b2baae [Sean Owen] Call SparkContext.stop() in all examples (and touch up minor nearby code style issues while at it)
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DecisionTreeRunner functionality additions:
* Allow user to pass in a test dataset
* Do not print full model if the model is too large.
As part of this, modify DecisionTreeModel and RandomForestModel to allow printing less info. Proposed updates:
* toString: prints model summary
* toDebugString: prints full model (named after RDD.toDebugString)
Similar update to Python API:
* __repr__() now prints a model summary
* toDebugString() now prints the full model
CC: mengxr chouqin manishamde codedeft Small update (whomever can take a look). Thanks!
Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>
Closes #2604 from jkbradley/dtrunner-update and squashes the following commits:
b2b3c60 [Joseph K. Bradley] re-added python sql doc test, temporarily removed before
07b1fae [Joseph K. Bradley] repr() now prints a model summary toDebugString() now prints the full model
1d0d93d [Joseph K. Bradley] Updated DT and RF to print less when toString is called. Added toDebugString for verbose printing.
22eac8c [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dtrunner-update
e007a95 [Joseph K. Bradley] Updated DecisionTreeRunner to accept a test dataset.
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This PR adds RandomForest to MLlib. The implementation is basic, and future performance optimizations will be important. (Note: RFs = Random Forests.)
# Overview
## RandomForest
* trains multiple trees at once to reduce the number of passes over the data
* allows feature subsets at each node
* uses a queue of nodes instead of fixed groups for each level
This implementation is based an implementation by manishamde and the [Alpine Labs Sequoia Forest](https://github.com/AlpineNow/SparkML2) by codedeft (in particular, the TreePoint, BaggedPoint, and node queue implementations). Thank you for your inputs!
## Testing
Correctness: This has been tested for correctness with the test suites and with DecisionTreeRunner on example datasets.
Performance: This has been performance tested using [this branch of spark-perf](https://github.com/jkbradley/spark-perf/tree/rfs). Results below.
### Regression tests for DecisionTree
Summary: For training 1 tree, there are small regressions, especially from feature subsampling.
In the table below, each row is a single (random) dataset. The 2 different sets of result columns are for 2 different RF implementations:
* (numTrees): This is from an earlier commit, after implementing RandomForest to train multiple trees at once. It does not include any code for feature subsampling.
* (feature subsets): This is from this current PR's code, after implementing feature subsampling.
These tests were to identify regressions in DecisionTree, so they are training 1 tree with all of the features (i.e., no feature subsampling).
These were run on an EC2 cluster with 15 workers, training 1 tree with maxDepth = 5 (= 6 levels). Speedup values < 1 indicate slowdowns from the old DecisionTree implementation.
numInstances | numFeatures | runtime (sec) | speedup | runtime (sec) | speedup
---- | ---- | ---- | ---- | ---- | ----
| | (numTrees) | (numTrees) | (feature subsets) | (feature subsets)
20000 | 100 | 4.051 | 1.044433473 | 4.478 | 0.9448414471
20000 | 500 | 8.472 | 1.104461756 | 9.315 | 1.004508857
20000 | 1500 | 19.354 | 1.05854087 | 20.863 | 0.9819776638
20000 | 3500 | 43.674 | 1.072033704 | 45.887 | 1.020332556
200000 | 100 | 4.196 | 1.171830315 | 4.848 | 1.014232673
200000 | 500 | 8.926 | 1.082791844 | 9.771 | 0.989151571
200000 | 1500 | 20.58 | 1.068415938 | 22.134 | 0.9934038131
200000 | 3500 | 48.043 | 1.075203464 | 52.249 | 0.9886505005
2000000 | 100 | 4.944 | 1.01355178 | 5.796 | 0.8645617667
2000000 | 500 | 11.11 | 1.016831683 | 12.482 | 0.9050632911
2000000 | 1500 | 31.144 | 1.017852556 | 35.274 | 0.8986789136
2000000 | 3500 | 79.981 | 1.085382778 | 101.105 | 0.8586123337
20000000 | 100 | 8.304 | 0.9270231214 | 9.073 | 0.8484514494
20000000 | 500 | 28.174 | 1.083268262 | 34.236 | 0.8914592826
20000000 | 1500 | 143.97 | 0.9579634646 | 159.275 | 0.8659111599
### Tests for forests
I have run other tests with numTrees=10 and with sqrt(numFeatures), and those indicate that multi-model training and feature subsets can speed up training for forests, especially when training deeper trees.
# Details on specific classes
## Changes to DecisionTree
* Main train() method is now in RandomForest.
* findBestSplits() is no longer needed. (It split levels into groups, but we now use a queue of nodes.)
* Many small changes to support RFs. (Note: These methods should be moved to RandomForest.scala in a later PR, but are in DecisionTree.scala to make code comparison easier.)
## RandomForest
* Main train() method is from old DecisionTree.
* selectNodesToSplit: Note that it selects nodes and feature subsets jointly to track memory usage.
## RandomForestModel
* Stores an Array[DecisionTreeModel]
* Prediction:
* For classification, most common label. For regression, mean.
* We could support other methods later.
## examples/.../DecisionTreeRunner
* This now takes numTrees and featureSubsetStrategy, to support RFs.
## DTStatsAggregator
* 2 types of functionality (w/ and w/o subsampling features): These require different indexing methods. (We could treat both as subsampling, but this is less efficient
DTStatsAggregator is now abstract, and 2 child classes implement these 2 types of functionality.
## impurities
* These now take instance weights.
## Node
* Some vals changed to vars.
* This is unfortunately a public API change (DeveloperApi). This could be avoided by creating a LearningNode struct, but would be awkward.
## RandomForestSuite
Please let me know if there are missing tests!
## BaggedPoint
This wraps TreePoint and holds bootstrap weights/counts.
# Design decisions
* BaggedPoint: BaggedPoint is separate from TreePoint since it may be useful for other bagging algorithms later on.
* RandomForest public API: What options should be easily supported by the train* methods? Should ALL options be in the Java-friendly constructors? Should there be a constructor taking Strategy?
* Feature subsampling options: What options should be supported? scikit-learn supports the same options, except for "onethird." One option would be to allow users to specific fractions ("0.1"): the current options could be supported, and any unrecognized values would be parsed as Doubles in [0,1].
* Splits and bins are computed before bootstrapping, so all trees use the same discretization.
* One queue, instead of one queue per tree.
CC: mengxr manishamde codedeft chouqin Please let me know if you have suggestions---thanks!
Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>
Author: qiping.lqp <qiping.lqp@alibaba-inc.com>
Author: chouqin <liqiping1991@gmail.com>
Closes #2435 from jkbradley/rfs-new and squashes the following commits:
c694174 [Joseph K. Bradley] Fixed typo
cc59d78 [Joseph K. Bradley] fixed imports
e25909f [Joseph K. Bradley] Simplified node group maps. Specifically, created NodeIndexInfo to store node index in agg and feature subsets, and no longer create extra maps in findBestSplits
fbe9a1e [Joseph K. Bradley] Changed default featureSubsetStrategy to be sqrt for classification, onethird for regression. Updated docs with references.
ef7c293 [Joseph K. Bradley] Updates based on code review. Most substantial changes: * Simplified DTStatsAggregator * Made RandomForestModel.trees public * Added test for regression to RandomForestSuite
593b13c [Joseph K. Bradley] Fixed bug in metadata for computing log2(num features). Now it checks >= 1.
a1a08df [Joseph K. Bradley] Removed old comments
866e766 [Joseph K. Bradley] Changed RandomForestSuite randomized tests to use multiple fixed random seeds.
ff8bb96 [Joseph K. Bradley] removed usage of null from RandomForest and replaced with Option
bf1a4c5 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new
6b79c07 [Joseph K. Bradley] Added RandomForestSuite, and fixed small bugs, style issues.
d7753d4 [Joseph K. Bradley] Added numTrees and featureSubsetStrategy to DecisionTreeRunner (to support RandomForest). Fixed bugs so that RandomForest now runs.
746d43c [Joseph K. Bradley] Implemented feature subsampling. Tested DecisionTree but not RandomForest.
6309d1d [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new. Added RandomForestModel.toString
b7ae594 [Joseph K. Bradley] Updated docs. Small fix for bug which does not cause errors: No longer allocate unused child nodes for leaf nodes.
121c74e [Joseph K. Bradley] Basic random forests are implemented. Random features per node not yet implemented. Test suite not implemented.
325d18a [Joseph K. Bradley] Merge branch 'chouqin-dt-preprune' into rfs-new
4ef9bf1 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new
61b2e72 [Joseph K. Bradley] Added max of 10GB for maxMemoryInMB in Strategy.
a95e7c8 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into chouqin-dt-preprune
6da8571 [Joseph K. Bradley] RFs partly implemented, not done yet
eddd1eb [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new
5c4ac33 [Joseph K. Bradley] Added check in Strategy to make sure minInstancesPerNode >= 1
0dd4d87 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dt-spark-3160
95c479d [Joseph K. Bradley] * Fixed typo in tree suite test "do not choose split that does not satisfy min instance per node requirements" * small style fixes
e2628b6 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into chouqin-dt-preprune
19b01af [Joseph K. Bradley] Merge remote-tracking branch 'chouqin/dt-preprune' into chouqin-dt-preprune
f1d11d1 [chouqin] fix typo
c7ebaf1 [chouqin] fix typo
39f9b60 [chouqin] change edge `minInstancesPerNode` to 2 and add one more test
c6e2dfc [Joseph K. Bradley] Added minInstancesPerNode and minInfoGain parameters to DecisionTreeRunner.scala and to Python API in tree.py
306120f [Joseph K. Bradley] Fixed typo in DecisionTreeModel.scala doc
eaa1dcf [Joseph K. Bradley] Added topNode doc in DecisionTree and scalastyle fix
d4d7864 [Joseph K. Bradley] Marked Node.build as deprecated
d4dbb99 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dt-spark-3160
1a8f0ad [Joseph K. Bradley] Eliminated pre-allocated nodes array in main train() method. * Nodes are constructed and added to the tree structure as needed during training.
0278a11 [chouqin] remove `noSplit` and set `Predict` private to tree
d593ec7 [chouqin] fix docs and change minInstancesPerNode to 1
2ab763b [Joseph K. Bradley] Simplifications to DecisionTree code:
efcc736 [qiping.lqp] fix bug
10b8012 [qiping.lqp] fix style
6728fad [qiping.lqp] minor fix: remove empty lines
bb465ca [qiping.lqp] Merge branch 'master' of https://github.com/apache/spark into dt-preprune
cadd569 [qiping.lqp] add api docs
46b891f [qiping.lqp] fix bug
e72c7e4 [qiping.lqp] add comments
845c6fa [qiping.lqp] fix style
f195e83 [qiping.lqp] fix style
987cbf4 [qiping.lqp] fix bug
ff34845 [qiping.lqp] separate calculation of predict of node from calculation of info gain
ac42378 [qiping.lqp] add min info gain and min instances per node parameters in decision tree
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https://issues.apache.org/jira/browse/SPARK-3389
Author: Uri Laserson <laserson@cloudera.com>
Closes #2256 from laserson/SPARK-3389 and squashes the following commits:
0ed363e [Uri Laserson] PEP8'd the python file
0b4b380 [Uri Laserson] Moved converter to examples and added python example
eecf4dc [Uri Laserson] [SPARK-3389] Add Converter for ease of Parquet reading in PySpark
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Author: Matthew Farrellee <matt@redhat.com>
Closes #2304 from mattf/SPARK-1701-partition-over-slice-for-python-examples and squashes the following commits:
928a581 [Matthew Farrellee] [SPARK-1701] [PySpark] remove slice terminology from python examples
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params to example and Python API
Added minInstancesPerNode, minInfoGain params to:
* DecisionTreeRunner.scala example
* Python API (tree.py)
Also:
* Fixed typo in tree suite test "do not choose split that does not satisfy min instance per node requirements"
* small style fixes
CC: mengxr
Author: qiping.lqp <qiping.lqp@alibaba-inc.com>
Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>
Author: chouqin <liqiping1991@gmail.com>
Closes #2349 from jkbradley/chouqin-dt-preprune and squashes the following commits:
61b2e72 [Joseph K. Bradley] Added max of 10GB for maxMemoryInMB in Strategy.
a95e7c8 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into chouqin-dt-preprune
95c479d [Joseph K. Bradley] * Fixed typo in tree suite test "do not choose split that does not satisfy min instance per node requirements" * small style fixes
e2628b6 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into chouqin-dt-preprune
19b01af [Joseph K. Bradley] Merge remote-tracking branch 'chouqin/dt-preprune' into chouqin-dt-preprune
f1d11d1 [chouqin] fix typo
c7ebaf1 [chouqin] fix typo
39f9b60 [chouqin] change edge `minInstancesPerNode` to 2 and add one more test
c6e2dfc [Joseph K. Bradley] Added minInstancesPerNode and minInfoGain parameters to DecisionTreeRunner.scala and to Python API in tree.py
0278a11 [chouqin] remove `noSplit` and set `Predict` private to tree
d593ec7 [chouqin] fix docs and change minInstancesPerNode to 1
efcc736 [qiping.lqp] fix bug
10b8012 [qiping.lqp] fix style
6728fad [qiping.lqp] minor fix: remove empty lines
bb465ca [qiping.lqp] Merge branch 'master' of https://github.com/apache/spark into dt-preprune
cadd569 [qiping.lqp] add api docs
46b891f [qiping.lqp] fix bug
e72c7e4 [qiping.lqp] add comments
845c6fa [qiping.lqp] fix style
f195e83 [qiping.lqp] fix style
987cbf4 [qiping.lqp] fix bug
ff34845 [qiping.lqp] separate calculation of predict of node from calculation of info gain
ac42378 [qiping.lqp] add min info gain and min instances per node parameters in decision tree
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...'t depend on
Publish local in maven term is `install`
and publish otherwise is `deploy`
So disabled both for following projects.
Author: Prashant Sharma <prashant.s@imaginea.com>
Closes #2329 from ScrapCodes/SPARK-3452/maven-skip-install and squashes the following commits:
257b79a [Prashant Sharma] [SPARK-3452] Maven build should skip publishing artifacts people shouldn't depend on
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Author: Prashant Sharma <prashant.s@imaginea.com>
Closes #2331 from ScrapCodes/compilation-warn and squashes the following commits:
44c1e76 [Prashant Sharma] Minor - Fix trivial compilation warnings.
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Adjust the default values of decision tree, based on the memory requirement discussed in https://github.com/apache/spark/pull/2125 :
1. maxMemoryInMB: 128 -> 256
2. maxBins: 100 -> 32
3. maxDepth: 4 -> 5 (in some example code)
jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes #2322 from mengxr/tree-defaults and squashes the following commits:
cda453a [Xiangrui Meng] fix tests
5900445 [Xiangrui Meng] update comments
8c81831 [Xiangrui Meng] update default values of tree:
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Author: GuoQiang Li <witgo@qq.com>
Closes #2268 from witgo/SPARK-3397 and squashes the following commits:
eaf913f [GuoQiang Li] Bump pom.xml version number of master branch to 1.2.0-SNAPSHOT
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This PR resolves [SPARK-3361](https://issues.apache.org/jira/browse/SPARK-3361) by expanding the PEP 8 checks to cover the remaining Python code base:
* The EC2 script
* All Python / PySpark examples
Author: Nicholas Chammas <nicholas.chammas@gmail.com>
Closes #2297 from nchammas/pep8-rulez and squashes the following commits:
1e5ac9a [Nicholas Chammas] PEP 8 fixes to Python examples
c3dbeff [Nicholas Chammas] PEP 8 fixes to EC2 script
65ef6e8 [Nicholas Chammas] expand PEP 8 checks
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#720
PR #720 made multiple changes to GraphGenerator.logNormalGraph including:
* Replacing the call to functions for generating random vertices and edges with in-line implementations with different equations. Based on reading the Pregel paper, I believe the in-line functions are incorrect.
* Hard-coding of RNG seeds so that method now generates the same graph for a given number of vertices, edges, mu, and sigma -- user is not able to override seed or specify that seed should be randomly generated.
* Backwards-incompatible change to logNormalGraph signature with introduction of new required parameter.
* Failed to update scala docs and programming guide for API changes
* Added a Synthetic Benchmark in the examples.
This PR:
* Removes the in-line calls and calls original vertex / edge generation functions again
* Adds an optional seed parameter for deterministic behavior (when desired)
* Keeps the number of partitions parameter that was added.
* Keeps compatibility with the synthetic benchmark example
* Maintains backwards-compatible API
Author: RJ Nowling <rnowling@gmail.com>
Author: Ankur Dave <ankurdave@gmail.com>
Closes #2168 from rnowling/graphgenrand and squashes the following commits:
f1cd79f [Ankur Dave] Style fixes
e11918e [RJ Nowling] Fix bad comparisons in unit tests
785ac70 [RJ Nowling] Fix style error
c70868d [RJ Nowling] Fix logNormalGraph scala doc for seed
41fd1f8 [RJ Nowling] Fix logNormalGraph scala doc for seed
799f002 [RJ Nowling] Added test for different seeds for sampleLogNormal
43949ad [RJ Nowling] Added test for different seeds for generateRandomEdges
2faf75f [RJ Nowling] Added unit test for logNormalGraph
82f22397 [RJ Nowling] Add unit test for sampleLogNormal
b99cba9 [RJ Nowling] Make sampleLogNormal private to Spark (vs private) for unit testing
6803da1 [RJ Nowling] Add GraphGeneratorsSuite with test for generateRandomEdges
1c8fc44 [RJ Nowling] Connected components part of SynthBenchmark was failing to call count on RDD before printing
dfbb6dd [RJ Nowling] Fix parameter name in SynthBenchmark docs
b5eeb80 [RJ Nowling] Add optional seed parameter to SynthBenchmark and set default to randomly generate a seed
1ff8d30 [RJ Nowling] Fix bug in generateRandomEdges where numVertices instead of numEdges was used to control number of edges to generate
98bb73c [RJ Nowling] Add documentation for logNormalGraph parameters
d40141a [RJ Nowling] Fix style error
684804d [RJ Nowling] revert PR #720 which introduce errors in logNormalGraph and messed up seeding of RNGs. Add user-defined optional seed for deterministic behavior
c183136 [RJ Nowling] Fix to deterministic GraphGenerators.logNormalGraph that allows generating graphs randomly using optional seed.
015010c [RJ Nowling] Fixed GraphGenerator logNormalGraph API to make backward-incompatible change in commit 894ecde04
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to support ~/spark/bin/run-example GraphXAnalytics triangles
/soc-LiveJournal1.txt --numEPart=256
Author: Larry Xiao <xiaodi@sjtu.edu.cn>
Closes #1766 from larryxiao/1986 and squashes the following commits:
bb77cd9 [Larry Xiao] [SPARK-1986][GraphX]move lib.Analytics to org.apache.spark.examples
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