- Nov 04, 2015
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Yanbo Liang authored
Like ml ```LinearRegression```, ```LogisticRegression``` should provide a training summary including feature names and their coefficients. Author: Yanbo Liang <ybliang8@gmail.com> Closes #9303 from yanboliang/spark-9492.
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tedyu authored
In the thread, http://search-hadoop.com/m/q3RTtcQiFSlTxeP/test+failed+due+to+OOME&subj=test+failed+due+to+OOME, it was discussed that memory consumption for SparkListenerSuite should be brought down. This is an attempt in that direction by reducing numSlices for local metrics test. Author: tedyu <yuzhihong@gmail.com> Closes #9384 from tedyu/master.
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jerryshao authored
This PR is based on the work of roji to support running Spark scripts from symlinks. Thanks for the great work roji . Would you mind taking a look at this PR, thanks a lot. For releases like HDP and others, normally it will expose the Spark executables as symlinks and put in `PATH`, but current Spark's scripts do not support finding real path from symlink recursively, this will make spark fail to execute from symlink. This PR try to solve this issue by finding the absolute path from symlink. Instead of using `readlink -f` like what this PR (https://github.com/apache/spark/pull/2386) implemented is that `-f` is not support for Mac, so here manually seeking the path through loop. I've tested with Mac and Linux (Cent OS), looks fine. This PR did not fix the scripts under `sbin` folder, not sure if it needs to be fixed also? Please help to review, any comment is greatly appreciated. Author: jerryshao <sshao@hortonworks.com> Author: Shay Rojansky <roji@roji.org> Closes #8669 from jerryshao/SPARK-2960.
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- Nov 03, 2015
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Wenchen Fan authored
depend on `caseSensitive` to do column name equality check, instead of just `==` Author: Wenchen Fan <wenchen@databricks.com> Closes #9410 from cloud-fan/partition.
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Nong authored
Author: Nong <nong@cloudera.com> Closes #9442 from nongli/spark-11483.
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lewuathe authored
Author: lewuathe <lewuathe@me.com> Author: Lewuathe <lewuathe@me.com> Closes #9394 from Lewuathe/missing-link-to-R-dataframe.
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Reynold Xin authored
We added a bunch of higher order statistics such as skewness and kurtosis to GroupedData. I don't think they are common enough to justify being listed, since users can always use the normal statistics aggregate functions. That is to say, after this change, we won't support ```scala df.groupBy("key").kurtosis("colA", "colB") ``` However, we will still support ```scala df.groupBy("key").agg(kurtosis(col("colA")), kurtosis(col("colB"))) ``` Author: Reynold Xin <rxin@databricks.com> Closes #9446 from rxin/SPARK-11489. -
Marcelo Vanzin authored
The test functionality should be the same, but without using mockito; logs don't really say anything useful but I suspect it may be the cause of the flakiness, since updating mocks when multiple threads may be using it doesn't work very well. It also allows some other cleanup (= less test code in FsHistoryProvider). Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #9425 from vanzin/SPARK-11466.
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Jacek Laskowski authored
Author: Jacek Laskowski <jacek.laskowski@deepsense.io> Closes #9444 from jaceklaskowski/TImely-fix.
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Wenchen Fan authored
Author: Wenchen Fan <wenchen@databricks.com> Closes #9434 from cloud-fan/rdd2ds and squashes the following commits: 0892d72 [Wenchen Fan] support create Dataset from RDD
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Davies Liu authored
Add Python API for stddev/stddev_pop/stddev_samp/variance/var_pop/var_samp/skewness/kurtosis Author: Davies Liu <davies@databricks.com> Closes #9424 from davies/py_var.
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felixcheung authored
 (This is without css, but you get the idea) shivaram Author: felixcheung <felixcheung_m@hotmail.com> Closes #9401 from felixcheung/rstudioprogrammingguide.
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Cheng Lian authored
This PR adds a new method `unhandledFilters` to `BaseRelation`. Data sources which implement this method properly may avoid the overhead of defensive filtering done by Spark SQL. Author: Cheng Lian <lian@databricks.com> Closes #9399 from liancheng/spark-10978.unhandled-filters.
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Mark Grover authored
Author: Mark Grover <grover.markgrover@gmail.com> Closes #8093 from markgrover/nm2.
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Yanbo Liang authored
Currently ```RFormula``` can only handle label with ```NumericType``` or ```BinaryType``` (cast it to ```DoubleType``` as the label of Linear Regression training), we should also support label of ```StringType``` which is needed for Logistic Regression (glm with family = "binomial"). For label of ```StringType```, we should use ```StringIndexer``` to transform it to 0-based index. Author: Yanbo Liang <ybliang8@gmail.com> Closes #9302 from yanboliang/spark-11349.
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Yanbo Liang authored
Rename ```regressionCoefficients``` back to ```coefficients```, and name ```weights``` to ```parameters```. See discussion [here](https://github.com/apache/spark/pull/9311/files#diff-e277fd0bc21f825d3196b4551c01fe5fR230). mengxr vectorijk dbtsai Author: Yanbo Liang <ybliang8@gmail.com> Closes #9431 from yanboliang/aft-coefficients.
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Yanbo Liang authored
https://issues.apache.org/jira/browse/SPARK-9836 Author: Yanbo Liang <ybliang8@gmail.com> Closes #9413 from yanboliang/spark-9836.
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Liang-Chi Hsieh authored
JIRA: https://issues.apache.org/jira/browse/SPARK-10304 This patch detects if the structure of partition directories is not valid. The test cases are from #8547. Thanks zhzhan. cc liancheng Author: Liang-Chi Hsieh <viirya@appier.com> Closes #8840 from viirya/detect_invalid_part_dir.
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Reynold Xin authored
Author: Reynold Xin <rxin@databricks.com> Closes #9219 from rxin/stage-cleanup1.
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Daoyuan Wang authored
https://issues.apache.org/jira/browse/SPARK-10533 val df = sqlContext.createDataFrame(Seq(("a",1.0),("b",2.0),("c",3.0))) df.filter("_2 < 2.0e1").show Scientific notation didn't work. Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #9085 from adrian-wang/scinotation.
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Jacek Lewandowski authored
DriverDescription refactored to case class because it included no mutable fields. ApplicationDescription had one mutable field, which was appUiUrl. This field was set by the driver to point to the driver web UI. Master was modifying this field when the application was removed to redirect requests to history server. This was wrong because objects which are sent over the wire should be immutable. Now appUiUrl is immutable in ApplicationDescription and always points to the driver UI even if it is already shutdown. The UI url which master exposes to the user and modifies dynamically is now included into ApplicationInfo - a data object which describes the application state internally in master. That URL in ApplicationInfo is initialised with the value from ApplicationDescription. ApplicationDescription also included value user, which is now a part of case class fields. Author: Jacek Lewandowski <lewandowski.jacek@gmail.com> Closes #9299 from jacek-lewandowski/SPARK-11344.
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Michael Armbrust authored
This PR adds a new method `groupBy(cols: Column*)` to `Dataset` that allows users to group using column expressions instead of a lambda function. Since the return type of these expressions is not known at compile time, we just set the key type as a generic `Row`. If the user would like to work the key in a type-safe way, they can call `grouped.asKey[Type]`, which is also added in this PR. ```scala val ds = Seq(("a", 10), ("a", 20), ("b", 1), ("b", 2), ("c", 1)).toDS() val grouped = ds.groupBy($"_1").asKey[String] val agged = grouped.mapGroups { case (g, iter) => Iterator((g, iter.map(_._2).sum)) } agged.collect() res0: Array(("a", 30), ("b", 3), ("c", 1)) ``` Author: Michael Armbrust <michael@databricks.com> Closes #9359 from marmbrus/columnGroupBy and squashes the following commits: bbcb03b [Michael Armbrust] Update DatasetSuite.scala 8fd2908 [Michael Armbrust] Update DatasetSuite.scala 0b0e2f8 [Michael Armbrust] [SPARK-11404] [SQL] Support for groupBy using column expressions -
Wenchen Fan authored
When we join 2 datasets, we will combine 2 encoders into a tupled one, and use it as the encoder for the jioned dataset. Assume both of the 2 encoders are flat, their `constructExpression`s both reference to the first element of input row. However, when we combine 2 encoders, the schema of input row changed, now the right encoder should reference to second element of input row. So we should rebind right encoder to let it know the new schema of input row before combine it. Author: Wenchen Fan <wenchen@databricks.com> Closes #9391 from cloud-fan/join and squashes the following commits: 846d3ab [Wenchen Fan] rebind right encoder when join 2 datasets
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Davies Liu authored
Right now, SQL's mutable projection updates every value of the mutable project after it evaluates the corresponding expression. This makes the behavior of MutableProjection confusing and complicate the implementation of common aggregate functions like stddev because developers need to be aware that when evaluating {{i+1}}th expression of a mutable projection, {{i}}th slot of the mutable row has already been updated. This PR make the MutableProjection atomic, by generating all the results of expressions first, then copy them into mutableRow. Had run a mircro-benchmark, there is no notable performance difference between using class members and local variables. cc yhuai Author: Davies Liu <davies@databricks.com> Closes #9422 from davies/atomic_mutable and squashes the following commits: bbc1758 [Davies Liu] support wide table 8a0ae14 [Davies Liu] fix bug bec07da [Davies Liu] refactor 2891628 [Davies Liu] make mutableProjection atomic -
Yin Huai authored
[SPARK-9858][SPARK-9859][SPARK-9861][SQL] Add an ExchangeCoordinator to estimate the number of post-shuffle partitions for aggregates and joins https://issues.apache.org/jira/browse/SPARK-9858 https://issues.apache.org/jira/browse/SPARK-9859 https://issues.apache.org/jira/browse/SPARK-9861 Author: Yin Huai <yhuai@databricks.com> Closes #9276 from yhuai/numReducer.
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navis.ryu authored
Hive GenericUDTF#initialize() defines field names in a returned schema though, the current HiveGenericUDTF drops these names. We might need to reflect these in a logical plan tree. Author: navis.ryu <navis@apache.org> Closes #8456 from navis/SPARK-9034.
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- Nov 02, 2015
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Yin Huai authored
This is the first task (https://issues.apache.org/jira/browse/SPARK-11469) of https://issues.apache.org/jira/browse/SPARK-11438 Author: Yin Huai <yhuai@databricks.com> Closes #9393 from yhuai/udfNondeterministic.
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Yves Raimond authored
Changes the personalized pagerank initialization to be non-uniform. Author: Yves Raimond <yraimond@netflix.com> Closes #9386 from moustaki/personalized-pagerank-init.
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Nong Li authored
1. Supporting expanding structs in Projections. i.e. "SELECT s.*" where s is a struct type. This is fixed by allowing the expand function to handle structs in addition to tables. 2. Supporting expanding * inside aggregate functions of structs. "SELECT max(struct(col1, structCol.*))" This requires recursively expanding the expressions. In this case, it it the aggregate expression "max(...)" and we need to recursively expand its children inputs. Author: Nong Li <nongli@gmail.com> Closes #9343 from nongli/spark-11329.
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Nong Li authored
…ering. For cached tables, we can just maintain the partitioning and ordering from the source relation. Author: Nong Li <nongli@gmail.com> Closes #9404 from nongli/spark-5354.
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DB Tsai authored
Removed the old `getModelWeights` function which was private and renamed into `getModelCoefficients` Author: DB Tsai <dbt@netflix.com> Closes #9426 from dbtsai/feature-minor.
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Calvin Jia authored
This is a reopening of #9204 which failed hadoop1 sbt tests. With the original PR, a classpath issue would occur due to the MIMA plugin pulling in hadoop-2.2 dependencies regardless of the hadoop version when building the `oldDeps` project. These affect the hadoop1 sbt build because they are placed in `lib_managed` and Tachyon 0.8.0's default hadoop version is 2.2. Author: Calvin Jia <jia.calvin@gmail.com> Closes #9395 from calvinjia/spark-11236.
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vectorijk authored
Deprecated in `LogisticRegression` and `LinearRegression` Author: vectorijk <jiangkai@gmail.com> Closes #9311 from vectorijk/spark-10592.
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Dominik Dahlem authored
mengxr, felixcheung This pull request just relaxes the type of the prediction/label columns to be float and double. Internally, these columns are casted to double. The other evaluators might need to be changed also. Author: Dominik Dahlem <dominik.dahlem@gmail.combination> Closes #9296 from dahlem/ddahlem_regression_evaluator_double_predictions_27102015.
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lihao authored
Author: lihao <lihaowhu@gmail.com> Closes #9275 from lidinghao/SPARK-10286.
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Rishabh Bhardwaj authored
[SPARK-11383][DOCS] Replaced example code in mllib-naive-bayes.md/mllib-isotonic-regression.md using include_example I have made the required changes in mllib-naive-bayes.md/mllib-isotonic-regression.md and also verified them. Kindle Review it. Author: Rishabh Bhardwaj <rbnext29@gmail.com> Closes #9353 from rishabhbhardwaj/SPARK-11383.
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tedyu authored
From Reynold in the thread 'Exception when using some aggregate operators' (http://search-hadoop.com/m/q3RTt0xFr22nXB4/): I don't think these are bugs. The SQL standard for average is "avg", not "mean". Similarly, a distinct count is supposed to be written as "count(distinct col)", not "countDistinct(col)". We can, however, make "mean" an alias for "avg" to improve compatibility between DataFrame and SQL. Author: tedyu <yuzhihong@gmail.com> Closes #9332 from ted-yu/master.
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Xiangrui Meng authored
This PR deprecates `runs` in k-means. `runs` introduces extra complexity and overhead in MLlib's k-means implementation. I haven't seen much usage with `runs` not equal to `1`. We don't have a unit test for it either. We can deprecate this method in 1.6, and void it in 1.7. It helps us simplify the implementation. cc: srowen Author: Xiangrui Meng <meng@databricks.com> Closes #9322 from mengxr/SPARK-11358.
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Sean Owen authored
Replace use of `junit.framework` with `org.junit`, and touch up tests in question Author: Sean Owen <sowen@cloudera.com> Closes #9411 from srowen/SPARK-11456.
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Jason White authored
When creating a DataFrame from an RDD in PySpark, `createDataFrame` calls `.take(10)` to verify the first 10 rows of the RDD match the provided schema. Similar to https://issues.apache.org/jira/browse/SPARK-8070, but that issue affected cases where a schema was not provided. Verifying the first 10 rows is of limited utility and causes the DAG to be executed non-lazily. If necessary, I believe this verification should be done lazily on all rows. However, since the caller is providing a schema to follow, I think it's acceptable to simply fail if the schema is incorrect. marmbrus We chatted about this at SparkSummitEU. davies you made a similar change for the infer-schema path in https://github.com/apache/spark/pull/6606 Author: Jason White <jason.white@shopify.com> Closes #9392 from JasonMWhite/createDataFrame_without_take.
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