### What changes were proposed in this pull request?
This PR replaces some references with correct ones (`:py:class:`).
### Why are the changes needed?
Newly added mixins from the original PR incorrectly reference classes with `:py:attr:`. While these classes are marked as internal, and not rendered in the standard documentation, it still makes sense to use correct roles.
### Does this PR introduce any user-facing change?
No. The changed part is not a part of generated PySpark documents.
### How was this patch tested?
Since this PR is a kind of typo fix, manually checking the patch.
We can build document for compilation test although there is no UI change.
Closes#26004 from zero323/SPARK-29142-FOLLOWUP.
Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
The Experimental and Evolving annotations are both (like Unstable) used to express that a an API may change. However there are many things in the code that have been marked that way since even Spark 1.x. Per the dev thread, anything introduced at or before Spark 2.3.0 is pretty much 'stable' in that it would not change without a deprecation cycle. Therefore I'd like to remove most of these annotations. And, remove the `:: Experimental ::` scaladoc tag too. And likewise for Python, R.
The changes below can be summarized as:
- Generally, anything introduced at or before Spark 2.3.0 has been unmarked as neither Evolving nor Experimental
- Obviously experimental items like DSv2, Barrier mode, ExperimentalMethods are untouched
- I _did_ unmark a few MLlib classes introduced in 2.4, as I am quite confident they're not going to change (e.g. KolmogorovSmirnovTest, PowerIterationClustering)
It's a big change to review, so I'd suggest scanning the list of _files_ changed to see if any area seems like it should remain partly experimental and examine those.
### Why are the changes needed?
Many of these annotations are incorrect; the APIs are de facto stable. Leaving them also makes legitimate usages of the annotations less meaningful.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Existing tests.
Closes#25558 from srowen/SPARK-28855.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
The hashSeed method allocates 64 bytes instead of 8. Other bytes are always zeros (thanks to default behavior of ByteBuffer). And they could be excluded from hash calculation because they don't differentiate inputs.
## How was this patch tested?
By running the existing tests - XORShiftRandomSuite
Closes#20793 from MaxGekk/hash-buff-size.
Lead-authored-by: Maxim Gekk <maxim.gekk@databricks.com>
Co-authored-by: Maxim Gekk <max.gekk@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Python version of https://github.com/apache/spark/pull/17654
## How was this patch tested?
Existing Python unit test
Closes#23676 from huaxingao/spark26754.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Add PMML export support for ML KMeans to PySpark.
## How was this patch tested?
Add tests in ml.tests.PersistenceTest.
Closes#23592 from huaxingao/spark-16838.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
The PR adds the `trainingCost` value to the `BisectingKMeansSummary`, in order to expose the information retrievable by running `computeCost` on the training dataset. This fills the gap with `KMeans` implementation.
## How was this patch tested?
improved UTs
Closes#22764 from mgaido91/SPARK-25765.
Authored-by: Marco Gaido <marcogaido91@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Add PowerIterationCluster (PIC) in R
## How was this patch tested?
Add test case
Closes#23072 from huaxingao/spark-19827.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
The PR removes the deprecated method `computeCost` of `KMeans`.
## How was this patch tested?
NA
Closes#22875 from mgaido91/SPARK-25867.
Authored-by: Marco Gaido <marcogaido91@gmail.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
Fix fastSquaredDistance to calculate dense-dense situation calculation performance problem and meanwhile enhance the calculation accuracy.
## How was this patch tested?
From different point to test after add this patch, the dense-dense calculation situation performance is enhanced and will do influence other calculation situation like (sparse-sparse, sparse-dense)
**For calculation logic test**
There is my test for sparse-sparse, dense-dense, sparse-dense case
There is test result:
First we need define some branch path logic for sparse-sparse and sparse-dense case
if meet precisionBound1, we define it as LOGIC1
if not meet precisionBound1, and not meet precisionBound2, we define it as LOGIC2
if not meet precisionBound1, but meet precisionBound2, we define it as LOGIC3
(There is a trick, you can manually change the precision value to meet above situation)
sparse- sparse case time cost situation (milliseconds)
LOGIC1
Before add patch: 7786, 7970, 8086
After add patch: 7729, 7653, 7903
LOGIC2
Before add patch: 8412, 9029, 8606
After add patch: 8603, 8724, 9024
LOGIC3
Before add patch: 19365, 19146, 19351
After add patch: 18917, 19007, 19074
sparse-dense case time cost situation (milliseconds)
LOGIC1
Before add patch: 4195, 4014, 4409
After add patch: 4081,3971, 4151
LOGIC2
Before add patch: 4968, 5579, 5080
After add patch: 4980, 5472, 5148
LOGIC3
Before add patch: 11848, 12077, 12168
After add patch: 11718, 11874, 11743
And for dense-dense case like we already discussed in comment, only use sqdist to calculate distance
dense-dense case time cost situation (milliseconds)
Before add patch: 7340, 7816, 7672
After add patch: 5752, 5800, 5753
**For real world data test**
There is my test data situation
I use the data
http://archive.ics.uci.edu/ml/datasets/Condition+monitoring+of+hydraulic+systems
extract file (PS1, PS2, PS3, PS4, PS5, PS6) to form the test data
total instances are 13230
the attributes for line are 6000
Result for sparse-sparse situation time cost (milliseconds)
Before Enhance: 7670, 7704, 7652
After Enhance: 7634, 7729, 7645
Closes#22893 from KyleLi1985/updatekmeanpatch.
Authored-by: 李亮 <liang.li.work@outlook.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
## What changes were proposed in this pull request?
The PR proposes to deprecate the `computeCost` method on `BisectingKMeans` in favor of the adoption of `ClusteringEvaluator` in order to evaluate the clustering.
## How was this patch tested?
NA
Closes#22869 from mgaido91/SPARK-25758_3.0.
Authored-by: Marco Gaido <marcogaido91@gmail.com>
Signed-off-by: DB Tsai <d_tsai@apple.com>
## What changes were proposed in this pull request?
The PR proposes to deprecate the `computeCost` method on `BisectingKMeans` in favor of the adoption of `ClusteringEvaluator` in order to evaluate the clustering.
## How was this patch tested?
NA
Closes#22756 from mgaido91/SPARK-25758.
Authored-by: Marco Gaido <marcogaido91@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
(This change is a subset of the changes needed for the JIRA; see https://github.com/apache/spark/pull/22231)
## What changes were proposed in this pull request?
Use raw strings and simpler regex syntax consistently in Python, which also avoids warnings from pycodestyle about accidentally relying Python's non-escaping of non-reserved chars in normal strings. Also, fix a few long lines.
## How was this patch tested?
Existing tests, and some manual double-checking of the behavior of regexes in Python 2/3 to be sure.
Closes#22400 from srowen/SPARK-25238.2.
Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
Fixing typos is sometimes very hard. It's not so easy to visually review them. Recently, I discovered a very useful tool for it, [misspell](https://github.com/client9/misspell).
This pull request fixes minor typos detected by [misspell](https://github.com/client9/misspell) except for the false positives. If you would like me to work on other files as well, let me know.
## How was this patch tested?
### before
```
$ misspell . | grep -v '.js'
R/pkg/R/SQLContext.R:354:43: "definiton" is a misspelling of "definition"
R/pkg/R/SQLContext.R:424:43: "definiton" is a misspelling of "definition"
R/pkg/R/SQLContext.R:445:43: "definiton" is a misspelling of "definition"
R/pkg/R/SQLContext.R:495:43: "definiton" is a misspelling of "definition"
NOTICE-binary:454:16: "containd" is a misspelling of "contained"
R/pkg/R/context.R:46:43: "definiton" is a misspelling of "definition"
R/pkg/R/context.R:74:43: "definiton" is a misspelling of "definition"
R/pkg/R/DataFrame.R:591:48: "persistance" is a misspelling of "persistence"
R/pkg/R/streaming.R:166:44: "occured" is a misspelling of "occurred"
R/pkg/inst/worker/worker.R:65:22: "ouput" is a misspelling of "output"
R/pkg/tests/fulltests/test_utils.R:106:25: "environemnt" is a misspelling of "environment"
common/kvstore/src/test/java/org/apache/spark/util/kvstore/InMemoryStoreSuite.java:38:39: "existant" is a misspelling of "existent"
common/kvstore/src/test/java/org/apache/spark/util/kvstore/LevelDBSuite.java:83:39: "existant" is a misspelling of "existent"
common/network-common/src/main/java/org/apache/spark/network/crypto/TransportCipher.java:243:46: "transfered" is a misspelling of "transferred"
common/network-common/src/main/java/org/apache/spark/network/sasl/SaslEncryption.java:234:19: "transfered" is a misspelling of "transferred"
common/network-common/src/main/java/org/apache/spark/network/sasl/SaslEncryption.java:238:63: "transfered" is a misspelling of "transferred"
common/network-common/src/main/java/org/apache/spark/network/sasl/SaslEncryption.java:244:46: "transfered" is a misspelling of "transferred"
common/network-common/src/main/java/org/apache/spark/network/sasl/SaslEncryption.java:276:39: "transfered" is a misspelling of "transferred"
common/network-common/src/main/java/org/apache/spark/network/util/AbstractFileRegion.java:27:20: "transfered" is a misspelling of "transferred"
common/unsafe/src/test/scala/org/apache/spark/unsafe/types/UTF8StringPropertyCheckSuite.scala:195:15: "orgin" is a misspelling of "origin"
core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala:621:39: "gauranteed" is a misspelling of "guaranteed"
core/src/main/scala/org/apache/spark/status/storeTypes.scala:113:29: "ect" is a misspelling of "etc"
core/src/main/scala/org/apache/spark/storage/DiskStore.scala:282:18: "transfered" is a misspelling of "transferred"
core/src/main/scala/org/apache/spark/util/ListenerBus.scala:64:17: "overriden" is a misspelling of "overridden"
core/src/test/scala/org/apache/spark/ShuffleSuite.scala:211:7: "substracted" is a misspelling of "subtracted"
core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala:1922:49: "agriculteur" is a misspelling of "agriculture"
core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala:2468:84: "truely" is a misspelling of "truly"
core/src/test/scala/org/apache/spark/storage/FlatmapIteratorSuite.scala:25:18: "persistance" is a misspelling of "persistence"
core/src/test/scala/org/apache/spark/storage/FlatmapIteratorSuite.scala:26:69: "persistance" is a misspelling of "persistence"
data/streaming/AFINN-111.txt:1219:0: "humerous" is a misspelling of "humorous"
dev/run-pip-tests:55:28: "enviroments" is a misspelling of "environments"
dev/run-pip-tests:91:37: "virutal" is a misspelling of "virtual"
dev/merge_spark_pr.py:377:72: "accross" is a misspelling of "across"
dev/merge_spark_pr.py:378:66: "accross" is a misspelling of "across"
dev/run-pip-tests:126:25: "enviroments" is a misspelling of "environments"
docs/configuration.md:1830:82: "overriden" is a misspelling of "overridden"
docs/structured-streaming-programming-guide.md:525:45: "processs" is a misspelling of "processes"
docs/structured-streaming-programming-guide.md:1165:61: "BETWEN" is a misspelling of "BETWEEN"
docs/sql-programming-guide.md:1891:810: "behaivor" is a misspelling of "behavior"
examples/src/main/python/sql/arrow.py:98:8: "substract" is a misspelling of "subtract"
examples/src/main/python/sql/arrow.py:103:27: "substract" is a misspelling of "subtract"
licenses/LICENSE-heapq.txt:5:63: "Stichting" is a misspelling of "Stitching"
licenses/LICENSE-heapq.txt:6:2: "Mathematisch" is a misspelling of "Mathematics"
licenses/LICENSE-heapq.txt:262:29: "Stichting" is a misspelling of "Stitching"
licenses/LICENSE-heapq.txt:262:39: "Mathematisch" is a misspelling of "Mathematics"
licenses/LICENSE-heapq.txt:269:49: "Stichting" is a misspelling of "Stitching"
licenses/LICENSE-heapq.txt:269:59: "Mathematisch" is a misspelling of "Mathematics"
licenses/LICENSE-heapq.txt:274:2: "STICHTING" is a misspelling of "STITCHING"
licenses/LICENSE-heapq.txt:274:12: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
licenses/LICENSE-heapq.txt:276:29: "STICHTING" is a misspelling of "STITCHING"
licenses/LICENSE-heapq.txt:276:39: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
licenses-binary/LICENSE-heapq.txt:5:63: "Stichting" is a misspelling of "Stitching"
licenses-binary/LICENSE-heapq.txt:6:2: "Mathematisch" is a misspelling of "Mathematics"
licenses-binary/LICENSE-heapq.txt:262:29: "Stichting" is a misspelling of "Stitching"
licenses-binary/LICENSE-heapq.txt:262:39: "Mathematisch" is a misspelling of "Mathematics"
licenses-binary/LICENSE-heapq.txt:269:49: "Stichting" is a misspelling of "Stitching"
licenses-binary/LICENSE-heapq.txt:269:59: "Mathematisch" is a misspelling of "Mathematics"
licenses-binary/LICENSE-heapq.txt:274:2: "STICHTING" is a misspelling of "STITCHING"
licenses-binary/LICENSE-heapq.txt:274:12: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
licenses-binary/LICENSE-heapq.txt:276:29: "STICHTING" is a misspelling of "STITCHING"
licenses-binary/LICENSE-heapq.txt:276:39: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
mllib/src/main/resources/org/apache/spark/ml/feature/stopwords/hungarian.txt:170:0: "teh" is a misspelling of "the"
mllib/src/main/resources/org/apache/spark/ml/feature/stopwords/portuguese.txt:53:0: "eles" is a misspelling of "eels"
mllib/src/main/scala/org/apache/spark/ml/stat/Summarizer.scala:99:20: "Euclidian" is a misspelling of "Euclidean"
mllib/src/main/scala/org/apache/spark/ml/stat/Summarizer.scala:539:11: "Euclidian" is a misspelling of "Euclidean"
mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala:77:36: "Teh" is a misspelling of "The"
mllib/src/main/scala/org/apache/spark/mllib/clustering/StreamingKMeans.scala:230:24: "inital" is a misspelling of "initial"
mllib/src/main/scala/org/apache/spark/mllib/stat/MultivariateOnlineSummarizer.scala:276:9: "Euclidian" is a misspelling of "Euclidean"
mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala:237:26: "descripiton" is a misspelling of "descriptions"
python/pyspark/find_spark_home.py:30:13: "enviroment" is a misspelling of "environment"
python/pyspark/context.py:937:12: "supress" is a misspelling of "suppress"
python/pyspark/context.py:938:12: "supress" is a misspelling of "suppress"
python/pyspark/context.py:939:12: "supress" is a misspelling of "suppress"
python/pyspark/context.py:940:12: "supress" is a misspelling of "suppress"
python/pyspark/heapq3.py:6:63: "Stichting" is a misspelling of "Stitching"
python/pyspark/heapq3.py:7:2: "Mathematisch" is a misspelling of "Mathematics"
python/pyspark/heapq3.py:263:29: "Stichting" is a misspelling of "Stitching"
python/pyspark/heapq3.py:263:39: "Mathematisch" is a misspelling of "Mathematics"
python/pyspark/heapq3.py:270:49: "Stichting" is a misspelling of "Stitching"
python/pyspark/heapq3.py:270:59: "Mathematisch" is a misspelling of "Mathematics"
python/pyspark/heapq3.py:275:2: "STICHTING" is a misspelling of "STITCHING"
python/pyspark/heapq3.py:275:12: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
python/pyspark/heapq3.py:277:29: "STICHTING" is a misspelling of "STITCHING"
python/pyspark/heapq3.py:277:39: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
python/pyspark/heapq3.py:713:8: "probabilty" is a misspelling of "probability"
python/pyspark/ml/clustering.py:1038:8: "Currenlty" is a misspelling of "Currently"
python/pyspark/ml/stat.py:339:23: "Euclidian" is a misspelling of "Euclidean"
python/pyspark/ml/regression.py:1378:20: "paramter" is a misspelling of "parameter"
python/pyspark/mllib/stat/_statistics.py:262:8: "probabilty" is a misspelling of "probability"
python/pyspark/rdd.py:1363:32: "paramter" is a misspelling of "parameter"
python/pyspark/streaming/tests.py:825:42: "retuns" is a misspelling of "returns"
python/pyspark/sql/tests.py:768:29: "initalization" is a misspelling of "initialization"
python/pyspark/sql/tests.py:3616:31: "initalize" is a misspelling of "initialize"
resource-managers/mesos/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendUtil.scala:120:39: "arbitary" is a misspelling of "arbitrary"
resource-managers/mesos/src/test/scala/org/apache/spark/deploy/mesos/MesosClusterDispatcherArgumentsSuite.scala:26:45: "sucessfully" is a misspelling of "successfully"
resource-managers/mesos/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerUtils.scala:358:27: "constaints" is a misspelling of "constraints"
resource-managers/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnClusterSuite.scala:111:24: "senstive" is a misspelling of "sensitive"
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/SessionCatalog.scala:1063:5: "overwirte" is a misspelling of "overwrite"
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala:1348:17: "compatability" is a misspelling of "compatibility"
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala:77:36: "paramter" is a misspelling of "parameter"
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala:1374:22: "precendence" is a misspelling of "precedence"
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala:238:27: "unnecassary" is a misspelling of "unnecessary"
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ConditionalExpressionSuite.scala:212:17: "whn" is a misspelling of "when"
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinHelper.scala:147:60: "timestmap" is a misspelling of "timestamp"
sql/core/src/test/scala/org/apache/spark/sql/TPCDSQuerySuite.scala:150:45: "precentage" is a misspelling of "percentage"
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVInferSchemaSuite.scala:135:29: "infered" is a misspelling of "inferred"
sql/hive/src/test/resources/golden/udf_instr-1-2e76f819563dbaba4beb51e3a130b922:1:52: "occurance" is a misspelling of "occurrence"
sql/hive/src/test/resources/golden/udf_instr-2-32da357fc754badd6e3898dcc8989182:1:52: "occurance" is a misspelling of "occurrence"
sql/hive/src/test/resources/golden/udf_locate-1-6e41693c9c6dceea4d7fab4c02884e4e:1:63: "occurance" is a misspelling of "occurrence"
sql/hive/src/test/resources/golden/udf_locate-2-d9b5934457931447874d6bb7c13de478:1:63: "occurance" is a misspelling of "occurrence"
sql/hive/src/test/resources/golden/udf_translate-2-f7aa38a33ca0df73b7a1e6b6da4b7fe8:9:79: "occurence" is a misspelling of "occurrence"
sql/hive/src/test/resources/golden/udf_translate-2-f7aa38a33ca0df73b7a1e6b6da4b7fe8:13:110: "occurence" is a misspelling of "occurrence"
sql/hive/src/test/resources/ql/src/test/queries/clientpositive/annotate_stats_join.q:46:105: "distint" is a misspelling of "distinct"
sql/hive/src/test/resources/ql/src/test/queries/clientpositive/auto_sortmerge_join_11.q:29:3: "Currenly" is a misspelling of "Currently"
sql/hive/src/test/resources/ql/src/test/queries/clientpositive/avro_partitioned.q:72:15: "existant" is a misspelling of "existent"
sql/hive/src/test/resources/ql/src/test/queries/clientpositive/decimal_udf.q:25:3: "substraction" is a misspelling of "subtraction"
sql/hive/src/test/resources/ql/src/test/queries/clientpositive/groupby2_map_multi_distinct.q:16:51: "funtion" is a misspelling of "function"
sql/hive/src/test/resources/ql/src/test/queries/clientpositive/groupby_sort_8.q:15:30: "issueing" is a misspelling of "issuing"
sql/hive/src/test/scala/org/apache/spark/sql/sources/HadoopFsRelationTest.scala:669:52: "wiht" is a misspelling of "with"
sql/hive-thriftserver/src/main/java/org/apache/hive/service/cli/session/HiveSessionImpl.java:474:9: "Refering" is a misspelling of "Referring"
```
### after
```
$ misspell . | grep -v '.js'
common/network-common/src/main/java/org/apache/spark/network/util/AbstractFileRegion.java:27:20: "transfered" is a misspelling of "transferred"
core/src/main/scala/org/apache/spark/status/storeTypes.scala:113:29: "ect" is a misspelling of "etc"
core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala:1922:49: "agriculteur" is a misspelling of "agriculture"
data/streaming/AFINN-111.txt:1219:0: "humerous" is a misspelling of "humorous"
licenses/LICENSE-heapq.txt:5:63: "Stichting" is a misspelling of "Stitching"
licenses/LICENSE-heapq.txt:6:2: "Mathematisch" is a misspelling of "Mathematics"
licenses/LICENSE-heapq.txt:262:29: "Stichting" is a misspelling of "Stitching"
licenses/LICENSE-heapq.txt:262:39: "Mathematisch" is a misspelling of "Mathematics"
licenses/LICENSE-heapq.txt:269:49: "Stichting" is a misspelling of "Stitching"
licenses/LICENSE-heapq.txt:269:59: "Mathematisch" is a misspelling of "Mathematics"
licenses/LICENSE-heapq.txt:274:2: "STICHTING" is a misspelling of "STITCHING"
licenses/LICENSE-heapq.txt:274:12: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
licenses/LICENSE-heapq.txt:276:29: "STICHTING" is a misspelling of "STITCHING"
licenses/LICENSE-heapq.txt:276:39: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
licenses-binary/LICENSE-heapq.txt:5:63: "Stichting" is a misspelling of "Stitching"
licenses-binary/LICENSE-heapq.txt:6:2: "Mathematisch" is a misspelling of "Mathematics"
licenses-binary/LICENSE-heapq.txt:262:29: "Stichting" is a misspelling of "Stitching"
licenses-binary/LICENSE-heapq.txt:262:39: "Mathematisch" is a misspelling of "Mathematics"
licenses-binary/LICENSE-heapq.txt:269:49: "Stichting" is a misspelling of "Stitching"
licenses-binary/LICENSE-heapq.txt:269:59: "Mathematisch" is a misspelling of "Mathematics"
licenses-binary/LICENSE-heapq.txt:274:2: "STICHTING" is a misspelling of "STITCHING"
licenses-binary/LICENSE-heapq.txt:274:12: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
licenses-binary/LICENSE-heapq.txt:276:29: "STICHTING" is a misspelling of "STITCHING"
licenses-binary/LICENSE-heapq.txt:276:39: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
mllib/src/main/resources/org/apache/spark/ml/feature/stopwords/hungarian.txt:170:0: "teh" is a misspelling of "the"
mllib/src/main/resources/org/apache/spark/ml/feature/stopwords/portuguese.txt:53:0: "eles" is a misspelling of "eels"
mllib/src/main/scala/org/apache/spark/ml/stat/Summarizer.scala:99:20: "Euclidian" is a misspelling of "Euclidean"
mllib/src/main/scala/org/apache/spark/ml/stat/Summarizer.scala:539:11: "Euclidian" is a misspelling of "Euclidean"
mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAOptimizer.scala:77:36: "Teh" is a misspelling of "The"
mllib/src/main/scala/org/apache/spark/mllib/stat/MultivariateOnlineSummarizer.scala:276:9: "Euclidian" is a misspelling of "Euclidean"
python/pyspark/heapq3.py:6:63: "Stichting" is a misspelling of "Stitching"
python/pyspark/heapq3.py:7:2: "Mathematisch" is a misspelling of "Mathematics"
python/pyspark/heapq3.py:263:29: "Stichting" is a misspelling of "Stitching"
python/pyspark/heapq3.py:263:39: "Mathematisch" is a misspelling of "Mathematics"
python/pyspark/heapq3.py:270:49: "Stichting" is a misspelling of "Stitching"
python/pyspark/heapq3.py:270:59: "Mathematisch" is a misspelling of "Mathematics"
python/pyspark/heapq3.py:275:2: "STICHTING" is a misspelling of "STITCHING"
python/pyspark/heapq3.py:275:12: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
python/pyspark/heapq3.py:277:29: "STICHTING" is a misspelling of "STITCHING"
python/pyspark/heapq3.py:277:39: "MATHEMATISCH" is a misspelling of "MATHEMATICS"
python/pyspark/ml/stat.py:339:23: "Euclidian" is a misspelling of "Euclidean"
```
Closes#22070 from seratch/fix-typo.
Authored-by: Kazuhiro Sera <seratch@gmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
## What changes were proposed in this pull request?
Add numIter to Python version of ClusteringSummary
## How was this patch tested?
Modified existing UT test_multiclass_logistic_regression_summary
Author: Huaxin Gao <huaxing@us.ibm.com>
Closes#21925 from huaxingao/spark-24973.
## What changes were proposed in this pull request?
Deprecate `KMeans.computeCost` which was introduced as a temp fix and now it is not needed anymore, since we introduced `ClusteringEvaluator`.
## How was this patch tested?
manual test (deprecation warning displayed)
Scala
```
...
scala> model.computeCost(dataset)
warning: there was one deprecation warning; re-run with -deprecation for details
res1: Double = 0.0
```
Python
```
>>> import warnings
>>> warnings.simplefilter('always', DeprecationWarning)
...
>>> model.computeCost(df)
/Users/mgaido/apache/spark/python/pyspark/ml/clustering.py:330: DeprecationWarning: Deprecated in 2.4.0. It will be removed in 3.0.0. Use ClusteringEvaluator instead.
" instead.", DeprecationWarning)
```
Author: Marco Gaido <marcogaido91@gmail.com>
Closes#20629 from mgaido91/SPARK-23451.
## What changes were proposed in this pull request?
add distanceMeasure to BisectingKMeans in Python.
## How was this patch tested?
added doctest and also manually tested it.
Author: Huaxin Gao <huaxing@us.ibm.com>
Closes#21557 from huaxingao/spark-24439.
## What changes were proposed in this pull request?
add spark.ml Python API for PIC
## How was this patch tested?
add doctest
Author: Huaxin Gao <huaxing@us.ibm.com>
Closes#21513 from huaxingao/spark--19826.
The exit() builtin is only for interactive use. applications should use sys.exit().
## What changes were proposed in this pull request?
All usage of the builtin `exit()` function is replaced by `sys.exit()`.
## How was this patch tested?
I ran `python/run-tests`.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Benjamin Peterson <benjamin@python.org>
Closes#20682 from benjaminp/sys-exit.
## What changes were proposed in this pull request?
SPARK-22119 introduced a new parameter for KMeans, ie. `distanceMeasure`. The PR adds it also to the Python interface.
## How was this patch tested?
added UTs
Author: Marco Gaido <marcogaido91@gmail.com>
Closes#20520 from mgaido91/SPARK-23344.
## What changes were proposed in this pull request?
Added call to copy values of Params from Estimator to Model after fit in PySpark ML. This will copy values for any params that are also defined in the Model. Since currently most Models do not define the same params from the Estimator, also added method to create new Params from looking at the Java object if they do not exist in the Python object. This is a temporary fix that can be removed once the PySpark models properly define the params themselves.
## How was this patch tested?
Refactored the `check_params` test to optionally check if the model params for Python and Java match and added this check to an existing fitted model that shares params between Estimator and Model.
Author: Bryan Cutler <cutlerb@gmail.com>
Closes#17849 from BryanCutler/pyspark-models-own-params-SPARK-10931.
## What changes were proposed in this pull request?
The `keyword_only` decorator in PySpark is not thread-safe. It writes kwargs to a static class variable in the decorator, which is then retrieved later in the class method as `_input_kwargs`. If multiple threads are constructing the same class with different kwargs, it becomes a race condition to read from the static class variable before it's overwritten. See [SPARK-19348](https://issues.apache.org/jira/browse/SPARK-19348) for reproduction code.
This change will write the kwargs to a member variable so that multiple threads can operate on separate instances without the race condition. It does not protect against multiple threads operating on a single instance, but that is better left to the user to synchronize.
## How was this patch tested?
Added new unit tests for using the keyword_only decorator and a regression test that verifies `_input_kwargs` can be overwritten from different class instances.
Author: Bryan Cutler <cutlerb@gmail.com>
Closes#16782 from BryanCutler/pyspark-keyword_only-threadsafe-SPARK-19348.
## What changes were proposed in this pull request?
add loglikelihood in GMM.summary
## How was this patch tested?
added tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Author: Ruifeng Zheng <ruifengz@foxmail.com>
Closes#12064 from zhengruifeng/gmm_metric.
## What changes were proposed in this pull request?
Copy `GaussianMixture` implementation from mllib to ml, then we can add new features to it.
I left mllib `GaussianMixture` untouched, unlike some other algorithms to wrap the ml implementation. For the following reasons:
- mllib `GaussianMixture` allows k == 1, but ml does not.
- mllib `GaussianMixture` supports setting initial model, but ml does not support currently. (We will definitely add this feature for ml in the future)
We can get around these issues to make mllib as a wrapper calling into ml, but I'd prefer to leave mllib untouched which can make ml clean.
Meanwhile, There is a big performance improvement for `GaussianMixture` in this PR. Since the covariance matrix of multivariate gaussian distribution is symmetric, we can only store the upper triangular part of the matrix and it will greatly reduce the shuffled data size. In my test, this change will reduce shuffled data size by about 50% and accelerate the job execution.
Before this PR:
![image](https://cloud.githubusercontent.com/assets/1962026/19641622/4bb017ac-9996-11e6-8ece-83db184b620a.png)
After this PR:
![image](https://cloud.githubusercontent.com/assets/1962026/19641635/629c21fe-9996-11e6-91e9-83ab74ae0126.png)
## How was this patch tested?
Existing tests and added new tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#15413 from yanboliang/spark-17847.
## What changes were proposed in this pull request?
There are many locations in the Spark repo where the same word occurs consecutively. Sometimes they are appropriately placed, but many times they are not. This PR removes the inappropriately duplicated words.
## How was this patch tested?
N/A since only docs or comments were updated.
Author: Niranjan Padmanabhan <niranjan.padmanabhan@gmail.com>
Closes#16455 from neurons/np.structure_streaming_doc.
## What changes were proposed in this pull request?
Add python api for KMeansSummary
## How was this patch tested?
unit test added
Author: Jeff Zhang <zjffdu@apache.org>
Closes#13557 from zjffdu/SPARK-15819.
## What changes were proposed in this pull request?
make a pass through the items marked as Experimental or DeveloperApi and see if any are stable enough to be unmarked. Also check for items marked final or sealed to see if they are stable enough to be opened up as APIs.
Some discussions in the jira: https://issues.apache.org/jira/browse/SPARK-18319
## How was this patch tested?
existing ut
Author: Yuhao <yuhao.yang@intel.com>
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes#15972 from hhbyyh/experimental21.
## What changes were proposed in this pull request?
Add model summary APIs for `GaussianMixtureModel` and `BisectingKMeansModel` in pyspark.
## How was this patch tested?
Unit tests.
Author: sethah <seth.hendrickson16@gmail.com>
Closes#15777 from sethah/pyspark_cluster_summaries.
## What changes were proposed in this pull request?
#14956 reduced default k-means|| init steps to 2 from 5 only for spark.mllib package, we should also do same change for spark.ml and PySpark.
## How was this patch tested?
Existing tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#15050 from yanboliang/spark-17389.
JIRA issue link:
https://issues.apache.org/jira/browse/SPARK-16961
Changed one line of Utils.randomizeInPlace to allow elements to stay in place.
Created a unit test that runs a Pearson's chi squared test to determine whether the output diverges significantly from a uniform distribution.
Author: Nick Lavers <nick.lavers@videoamp.com>
Closes#14551 from nicklavers/SPARK-16961-randomizeInPlace.
## What changes were proposed in this pull request?
Now we have PySpark picklers for new and old vector/matrix, individually. However, they are all implemented under `PythonMLlibAPI`. To separate spark.mllib from spark.ml, we should implement the picklers of new vector/matrix under `spark.ml.python` instead.
## How was this patch tested?
Existing tests.
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Closes#13219 from viirya/pyspark-pickler-ml.
## What changes were proposed in this pull request?
Since we done Scala API audit for ml.clustering at #13148, we should also fix and update the corresponding Python API docs to keep them in sync.
## How was this patch tested?
Docs change, no tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#13291 from yanboliang/spark-15361-followup.
## What changes were proposed in this pull request?
Replace SQLContext and SparkContext with SparkSession using builder pattern in python test code.
## How was this patch tested?
Existing test.
Author: WeichenXu <WeichenXu123@outlook.com>
Closes#13242 from WeichenXu123/python_doctest_update_sparksession.
## What changes were proposed in this pull request?
Once SPARK-14487 and SPARK-14549 are merged, we will migrate to use the new vector and matrix type in the new ml pipeline based apis.
## How was this patch tested?
Unit tests
Author: DB Tsai <dbt@netflix.com>
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes#12627 from dbtsai/SPARK-14615-NewML.
## What changes were proposed in this pull request?
1, add arg-checkings for `tol` and `stepSize` to keep in line with `SharedParamsCodeGen.scala`
2, fix one typo
## How was this patch tested?
local build
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes#12996 from zhengruifeng/py_args_checking.
## What changes were proposed in this pull request?
PySpark ML Params setter code clean up.
For examples,
```setInputCol``` can be simplified from
```
self._set(inputCol=value)
return self
```
to:
```
return self._set(inputCol=value)
```
This is a pretty big sweeps, and we cleaned wherever possible.
## How was this patch tested?
Exist unit tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#12749 from yanboliang/spark-14971.
## What changes were proposed in this pull request?
pyspark.ml API for LDA
* LDA, LDAModel, LocalLDAModel, DistributedLDAModel
* includes persistence
This replaces [https://github.com/apache/spark/pull/10242]
## How was this patch tested?
* doc test for LDA, including Param setters
* unit test for persistence
Author: Joseph K. Bradley <joseph@databricks.com>
Author: Jeff Zhang <zjffdu@apache.org>
Closes#12723 from jkbradley/zjffdu-SPARK-11940.
## What changes were proposed in this pull request?
Before, spark.ml GaussianMixtureModel used the spark.mllib MultivariateGaussian in its public API. This was added after 1.6, so we can modify this API without breaking APIs.
This PR copies MultivariateGaussian to mllib-local in spark.ml, with a few changes:
* Renamed fields to match numpy, scipy: mu => mean, sigma => cov
This PR then uses the spark.ml MultivariateGaussian in the spark.ml GaussianMixtureModel, which involves:
* Modifying the constructor
* Adding a computeProbabilities method
Also:
* Added EPSILON to mllib-local for use in MultivariateGaussian
## How was this patch tested?
Existing unit tests
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#12593 from jkbradley/sparkml-gmm-fix.
## What changes were proposed in this pull request?
We deprecated ```runs``` of mllib.KMeans in Spark 1.6 (SPARK-11358). In 2.0, we will make it no effect (with warning messages). We did not remove ```setRuns/getRuns``` for better binary compatibility.
This PR change `runs` which are appeared at the public API. Usage inside of ```KMeans.runAlgorithm()``` will be resolved at #10806.
## How was this patch tested?
Existing unit tests.
cc jkbradley
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#12608 from yanboliang/spark-11559.
## What changes were proposed in this pull request?
Add Python API in ML for GaussianMixture
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
Add doctest and test cases are the same as mllib Python tests
./dev/lint-python
PEP8 checks passed.
rm -rf _build/*
pydoc checks passed.
./python/run-tests --python-executables=python2.7 --modules=pyspark-ml
Running PySpark tests. Output is in /Users/mwang/spark_ws_0904/python/unit-tests.log
Will test against the following Python executables: ['python2.7']
Will test the following Python modules: ['pyspark-ml']
Finished test(python2.7): pyspark.ml.evaluation (18s)
Finished test(python2.7): pyspark.ml.clustering (40s)
Finished test(python2.7): pyspark.ml.classification (49s)
Finished test(python2.7): pyspark.ml.recommendation (44s)
Finished test(python2.7): pyspark.ml.feature (64s)
Finished test(python2.7): pyspark.ml.regression (45s)
Finished test(python2.7): pyspark.ml.tuning (30s)
Finished test(python2.7): pyspark.ml.tests (56s)
Tests passed in 106 seconds
Author: wm624@hotmail.com <wm624@hotmail.com>
Closes#12402 from wangmiao1981/gmm.
## What changes were proposed in this pull request?
This patch provides a first cut of python APIs for structured streaming. This PR provides the new classes:
- ContinuousQuery
- Trigger
- ProcessingTime
in pyspark under `pyspark.sql.streaming`.
In addition, it contains the new methods added under:
- `DataFrameWriter`
a) `startStream`
b) `trigger`
c) `queryName`
- `DataFrameReader`
a) `stream`
- `DataFrame`
a) `isStreaming`
This PR doesn't contain all methods exposed for `ContinuousQuery`, for example:
- `exception`
- `sourceStatuses`
- `sinkStatus`
They may be added in a follow up.
This PR also contains some very minor doc fixes in the Scala side.
## How was this patch tested?
Python doc tests
TODO:
- [ ] verify Python docs look good
Author: Burak Yavuz <brkyvz@gmail.com>
Author: Burak Yavuz <burak@databricks.com>
Closes#12320 from brkyvz/stream-python.
## What changes were proposed in this pull request?
PySpark Param constructors need to pass the TypeConverter argument by name, partly to make sure it is not mistaken for the expectedType arg and partly because we will remove the expectedType arg in 2.1. In several places, this is not being done correctly.
This PR changes all usages in pyspark/ml/ to keyword args.
## How was this patch tested?
Existing unit tests. I will not test type conversion for every Param unless we really think it necessary.
Also, if you start the PySpark shell and import classes (e.g., pyspark.ml.feature.StandardScaler), then you no longer get this warning:
```
/Users/josephkb/spark/python/pyspark/ml/param/__init__.py:58: UserWarning: expectedType is deprecated and will be removed in 2.1. Use typeConverter instead, as a keyword argument.
"Use typeConverter instead, as a keyword argument.")
```
That warning came from the typeConverter argument being passes as the expectedType arg by mistake.
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#12480 from jkbradley/typeconverter-fix.
## What changes were proposed in this pull request?
Param setters in python previously accessed the _paramMap directly to update values. The `_set` method now implements type checking, so it should be used to update all parameters. This PR eliminates all direct accesses to `_paramMap` besides the one in the `_set` method to ensure type checking happens.
Additional changes:
* [SPARK-13068](https://github.com/apache/spark/pull/11663) missed adding type converters in evaluation.py so those are done here
* An incorrect `toBoolean` type converter was used for StringIndexer `handleInvalid` param in previous PR. This is fixed here.
## How was this patch tested?
Existing unit tests verify that parameters are still set properly. No new functionality is actually added in this PR.
Author: sethah <seth.hendrickson16@gmail.com>
Closes#11939 from sethah/SPARK-14104.
## What changes were proposed in this pull request?
PySpark ml.clustering BisectingKMeans support export/import
## How was this patch tested?
doc test.
cc jkbradley
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#12112 from yanboliang/spark-14305.
## What changes were proposed in this pull request?
This patch adds type conversion functionality for parameters in Pyspark. A `typeConverter` field is added to the constructor of `Param` class. This argument is a function which converts values passed to this param to the appropriate type if possible. This is beneficial so that the params can fail at set time if they are given inappropriate values, but even more so because coherent error messages are now provided when Py4J cannot cast the python type to the appropriate Java type.
This patch also adds a `TypeConverters` class with factory methods for common type conversions. Most of the changes involve adding these factory type converters to existing params. The previous solution to this issue, `expectedType`, is deprecated and can be removed in 2.1.0 as discussed on the Jira.
## How was this patch tested?
Unit tests were added in python/pyspark/ml/tests.py to test parameter type conversion. These tests check that values that should be convertible are converted correctly, and that the appropriate errors are thrown when invalid values are provided.
Author: sethah <seth.hendrickson16@gmail.com>
Closes#11663 from sethah/SPARK-13068-tc.
Adds support for saving and loading nested ML Pipelines from Python. Pipeline and PipelineModel do not extend JavaWrapper, but they are able to utilize the JavaMLWriter, JavaMLReader implementations.
Also:
* Separates out interfaces from Java wrapper implementations for MLWritable, MLReadable, MLWriter, MLReader.
* Moves methods _stages_java2py, _stages_py2java into Pipeline, PipelineModel as _transfer_stage_from_java, _transfer_stage_to_java
Added new unit test for nested Pipelines. Abstracted validity check into a helper method for the 2 unit tests.
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#11866 from jkbradley/nested-pipeline-io.
Closes#11835
This is to fix a long-time annoyance: Whenever we add a new algorithm to pyspark.ml, we have to add it to the ```__all__``` list at the top. Since we keep it alphabetized, it often creates a lot more changes than needed. It is also easy to add the Estimator and forget the Model. I'm going to switch it to have one algorithm per line.
This also alphabetizes a few out-of-place classes in pyspark.ml.feature. No changes have been made to the moved classes.
CC: thunterdb
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#10927 from jkbradley/ml-python-all-list.