Move insertInto to write. Also, remove the partition columns from InsertIntoHadoopFsRelation. #16
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This case clause is already covered by the one above, and generates a compilation warning. Author: Cheng Lian <lian@databricks.com> Closes apache#6214 from liancheng/remove-unreachable-code and squashes the following commits: c38ca7c [Cheng Lian] Removes an unreachable case clause
cc pwendell P.S: I can't believe this was outdated all along ? Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu> Closes apache#6215 from shivaram/update-ec2-map and squashes the following commits: ae3937a [Shivaram Venkataraman] Add 1.3, 1.3.1 to master branch EC2 scripts
Author: scwf <wangfei1@huawei.com> Closes apache#6145 from scwf/InConversion and squashes the following commits: 5c8ac6b [scwf] minir fix for InConversion
… deserialized JIRA: https://issues.apache.org/jira/browse/SPARK-7447 `MetadataCache` in `ParquetRelation2` is annotated as `transient`. When `ParquetRelation2` is deserialized, we ask `MetadataCache` to refresh and perform schema merging again. It is time-consuming especially for very many parquet files. With the new `FSBasedParquetRelation`, although `MetadataCache` is not `transient` now, `MetadataCache.refresh()` still performs schema merging again when the relation is deserialized. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes apache#6012 from viirya/without_remerge_schema and squashes the following commits: 2663957 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into without_remerge_schema 6ac7d93 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into without_remerge_schema b0fc09b [Liang-Chi Hsieh] Don't generate and merge parquetSchema multiple times.
This adds a new profile, `hadoop-2.6`, copying over the hadoop-2.4 properties, updating ZK to 3.4.6 and making the curator version a configurable option. That keeps the curator-recipes JAR in sync with that used in hadoop. There's one more option to consider: making the full curator-client version explicit with its own dependency version. This will pin down the version from hadoop and hive imports Author: Steve Loughran <stevel@hortonworks.com> Closes apache#6191 from steveloughran/stevel/SPARK-7669-hadoop-2.6 and squashes the following commits: e3e281a [Steve Loughran] SPARK-7669 declare the version of curator-client and curator-framework JARs 2901ea9 [Steve Loughran] SPARK-7669 Builds against Hadoop 2.6+ get inconsistent curator dependencies
This patch wraps `SnappyOutputStream` to ensure that `close()` is idempotent and to guard against write-after-`close()` bugs. This is a workaround for xerial/snappy-java#107, a bug where a non-idempotent `close()` method can lead to stream corruption. We can remove this workaround if we upgrade to a snappy-java version that contains my fix for this bug, but in the meantime this patch offers a backportable Spark fix. Author: Josh Rosen <joshrosen@databricks.com> Closes apache#6176 from JoshRosen/SPARK-7660-wrap-snappy and squashes the following commits: 8b77aae [Josh Rosen] Wrap SnappyOutputStream to fix SPARK-7660
…s in SparkStrategies In `SparkStrategies`, `RunnableDescribeCommand` is called with the output attributes of the table being described rather than the attributes for the `describe` command's output. I discovered this issue because it caused type conversion errors in some UnsafeRow conversion code that I'm writing. Author: Josh Rosen <joshrosen@databricks.com> Closes apache#6217 from JoshRosen/SPARK-7686 and squashes the following commits: 953a344 [Josh Rosen] Fix SPARK-7686 with a simple change in SparkStrategies. a4eec9f [Josh Rosen] Add failing regression test for SPARK-7686
Author: Michael Armbrust <michael@databricks.com> Closes apache#6167 from marmbrus/configureIsolation and squashes the following commits: 6147cbe [Michael Armbrust] filter other conf 22cc3bc [Michael Armbrust] Merge remote-tracking branch 'origin/master' into configureIsolation 07476ee [Michael Armbrust] filter empty prefixes dfdf19c [Michael Armbrust] [SPARK-6906][SQL] Allow configuration of classloader isolation for hive
…SIS] Updates to the Kinesis API SPARK-6514 - Use correct region SPARK-5960 - Allow AWS Credentials to be directly passed SPARK-6656 - Specify kinesis application name explicitly SPARK-7679 - Upgrade to latest KCL and AWS SDK. Author: Tathagata Das <tathagata.das1565@gmail.com> Closes apache#6147 from tdas/kinesis-api-update and squashes the following commits: f23ea77 [Tathagata Das] Updated versions and updated APIs 373b201 [Tathagata Das] Updated Kinesis API
It's a follow-up of apache#5154, we can speed up scala udf evaluation by create type converter in advance. Author: Wenchen Fan <cloud0fan@outlook.com> Closes apache#6182 from cloud-fan/tmp and squashes the following commits: 241cfe9 [Wenchen Fan] use converter in ScalaUdf
…mplicits.global" Learnt a lesson from SPARK-7655: Spark should avoid to use `scala.concurrent.ExecutionContext.Implicits.global` because the user may submit blocking actions to `scala.concurrent.ExecutionContext.Implicits.global` and exhaust all threads in it. This could crash Spark. So Spark should always use its own thread pools for safety. This PR removes all usages of `scala.concurrent.ExecutionContext.Implicits.global` and uses proper thread pools to replace them. Author: zsxwing <zsxwing@gmail.com> Closes apache#6223 from zsxwing/SPARK-7693 and squashes the following commits: a33ff06 [zsxwing] Decrease the max thread number from 1024 to 128 cf4b3fc [zsxwing] Remove "import scala.concurrent.ExecutionContext.Implicits.global"
The `toString` method of `LogisticRegressionModel` calls `get` method on an Option (threshold) without a safeguard. In spark-shell, the following code `val model = algorithm.run(data).clearThreshold()` in lbfgs code will fail as `toString `method will be called right after `clearThreshold()` to show the results in the REPL. Author: Shuo Xiang <shuoxiangpub@gmail.com> Closes apache#6224 from coderxiang/getorelse and squashes the following commits: d5f53c9 [Shuo Xiang] use getOrElse for getting the threshold of LR model 5f109b4 [Shuo Xiang] Merge remote-tracking branch 'upstream/master' c5c5bfe [Shuo Xiang] Merge remote-tracking branch 'upstream/master' 98804c9 [Shuo Xiang] fix bug in topBykey and update test
…BC metadata instead of returned BigDecimal JIRA: https://issues.apache.org/jira/browse/SPARK-7299 When connecting with oracle db through jdbc, the precision and scale of `BigDecimal` object returned by `ResultSet.getBigDecimal` is not correctly matched to the table schema reported by `ResultSetMetaData.getPrecision` and `ResultSetMetaData.getScale`. So in case you insert a value like `19999` into a column with `NUMBER(12, 2)` type, you get through a `BigDecimal` object with scale as 0. But the dataframe schema has correct type as `DecimalType(12, 2)`. Thus, after you save the dataframe into parquet file and then retrieve it, you will get wrong result `199.99`. Because it is reported to be problematic on jdbc connection with oracle db. It might be difficult to add test case for it. But according to the user's test on JIRA, it solves this problem. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes apache#5833 from viirya/jdbc_decimal_precision and squashes the following commits: 69bc2b5 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into jdbc_decimal_precision 928f864 [Liang-Chi Hsieh] Add comments. 5f9da94 [Liang-Chi Hsieh] Set up Decimal's precision and scale according to table schema instead of returned BigDecimal.
Fixed the following warnings in `make clean html` under `python/docs`: ~~~ /Users/meng/src/spark/python/pyspark/mllib/evaluation.py:docstring of pyspark.mllib.evaluation.RankingMetrics.ndcgAt:3: ERROR: Unexpected indentation. /Users/meng/src/spark/python/pyspark/mllib/evaluation.py:docstring of pyspark.mllib.evaluation.RankingMetrics.ndcgAt:4: WARNING: Block quote ends without a blank line; unexpected unindent. /Users/meng/src/spark/python/pyspark/mllib/fpm.py:docstring of pyspark.mllib.fpm.FPGrowth.train:3: ERROR: Unexpected indentation. /Users/meng/src/spark/python/pyspark/mllib/fpm.py:docstring of pyspark.mllib.fpm.FPGrowth.train:4: WARNING: Block quote ends without a blank line; unexpected unindent. /Users/meng/src/spark/python/pyspark/sql/__init__.py:docstring of pyspark.sql.DataFrame.replace:16: WARNING: Field list ends without a blank line; unexpected unindent. /Users/meng/src/spark/python/pyspark/streaming/kafka.py:docstring of pyspark.streaming.kafka.KafkaUtils.createRDD:8: ERROR: Unexpected indentation. /Users/meng/src/spark/python/pyspark/streaming/kafka.py:docstring of pyspark.streaming.kafka.KafkaUtils.createRDD:9: WARNING: Block quote ends without a blank line; unexpected unindent. ~~~ davies Author: Xiangrui Meng <meng@databricks.com> Closes apache#6221 from mengxr/SPARK-6657 and squashes the following commits: e3f83fe [Xiangrui Meng] fix sql and streaming doc warnings 2b4371e [Xiangrui Meng] fix mllib python doc warnings
https://issues.apache.org/jira/browse/SPARK-7272 Author: Vincenzo Selvaggio <vselvaggio@hotmail.it> Closes apache#6219 from selvinsource/mllib_pmml_model_export_SPARK-7272 and squashes the following commits: c866fb8 [Vincenzo Selvaggio] Update mllib-pmml-model-export.md 1beda98 [Vincenzo Selvaggio] [SPARK-7272] Initial user guide for pmml export d670662 [Vincenzo Selvaggio] Update mllib-pmml-model-export.md 2731375 [Vincenzo Selvaggio] Update mllib-pmml-model-export.md 680dc33 [Vincenzo Selvaggio] Update mllib-pmml-model-export.md 2e298b5 [Vincenzo Selvaggio] Update mllib-pmml-model-export.md a932f51 [Vincenzo Selvaggio] Create mllib-pmml-model-export.md
This patch fixes two things: **SPARK-7627.** Cached RDDs no longer light up on the job page. This is a simple fix. **SPARK-7472.** Display skipped stages differently from normal stages. The latter is a major UX issue. Because we link the job viz to the stage viz even for skipped stages, the user may inadvertently click into the stage page of a skipped stage, which is empty. ------------------- <img src="https://cloud.githubusercontent.com/assets/2133137/7675241/de1a3da6-fcea-11e4-8101-88055cef78c5.png" width="300px" /> Author: Andrew Or <andrew@databricks.com> Closes apache#6171 from andrewor14/dag-viz-skipped and squashes the following commits: f261797 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-skipped 0eda358 [Andrew Or] Tweak skipped stage border color c604150 [Andrew Or] Tweak grayscale colors 7010676 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-skipped 762b541 [Andrew Or] Use special prefix for stage clusters to avoid collisions 51c95b9 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-skipped b928cd4 [Andrew Or] Fix potential leak + write tests for it 7c4c364 [Andrew Or] Show skipped stages differently 7cc34ce [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-skipped c121fa2 [Andrew Or] Fix cache color
Replace the DriverQuirks with JdbcDialect(s) (and MySQLDialect/PostgresDialect) and allow developers to change the dialects on the fly (for new JDBCRRDs only). Some types (like an unsigned 64bit number) can be trivially mapped to java. The status quo is that the RRD will fail to load. This patch makes it possible to overwrite the type mapping to read e.g. 64Bit numbers as strings and handle them afterwards in software. JDBCSuite has an example that maps all types to String, which should always work (at the cost of extra code afterwards). As a side effect it should now be possible to develop simple dialects out-of-tree and even with spark-shell. Author: Rene Treffer <treffer@measite.de> Closes apache#5555 from rtreffer/jdbc-dialects and squashes the following commits: 3cbafd7 [Rene Treffer] [SPARK-6888] ignore classes belonging to changed API in MIMA report fe7e2e8 [Rene Treffer] [SPARK-6888] Make the jdbc driver handling user-definable
<!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/6091) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes apache#6091 from liancheng/spark-7570 and squashes the following commits: 8ff07e8 [Cheng Lian] Ignores _temporary during partition discovery
Author: Wenchen Fan <cloud0fan@outlook.com> Closes apache#6235 from cloud-fan/tmp and squashes the following commits: 8f16367 [Wenchen Fan] use private[this]
This PR makes pipeline stages in Python copyable and hence simplifies some implementations. It also includes the following changes: 1. Rename `paramMap` and `defaultParamMap` to `_paramMap` and `_defaultParamMap`, respectively. 2. Accept a list of param maps in `fit`. 3. Use parent uid and name to identify param. jkbradley Author: Xiangrui Meng <meng@databricks.com> Author: Joseph K. Bradley <joseph@databricks.com> Closes apache#6088 from mengxr/SPARK-7380 and squashes the following commits: 413c463 [Xiangrui Meng] remove unnecessary doc 4159f35 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7380 611c719 [Xiangrui Meng] fix python style 68862b8 [Xiangrui Meng] update _java_obj initialization 927ad19 [Xiangrui Meng] fix ml/tests.py 0138fc3 [Xiangrui Meng] update feature transformers and fix a bug in RegexTokenizer 9ca44fb [Xiangrui Meng] simplify Java wrappers and add tests c7d84ef [Xiangrui Meng] update ml/tests.py to test copy params 7e0d27f [Xiangrui Meng] merge master 46840fb [Xiangrui Meng] update wrappers b6db1ed [Xiangrui Meng] update all self.paramMap to self._paramMap 46cb6ed [Xiangrui Meng] merge master a163413 [Xiangrui Meng] fix style 1042e80 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7380 9630eae [Xiangrui Meng] fix Identifiable._randomUID 13bd70a [Xiangrui Meng] update ml/tests.py 64a536c [Xiangrui Meng] use _fit/_transform/_evaluate to simplify the impl 02abf13 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into copyable-python 66ce18c [Joseph K. Bradley] some cleanups before sending to Xiangrui 7431272 [Joseph K. Bradley] Rebased with master
This PR updates PR apache#6135 authored by zhzhan from Hortonworks. ---- This PR implements a Spark SQL data source for accessing ORC files. > **NOTE** > > Although ORC is now an Apache TLP, the codebase is still tightly coupled with Hive. That's why the new ORC data source is under `org.apache.spark.sql.hive` package, and must be used with `HiveContext`. However, it doesn't require existing Hive installation to access ORC files. 1. Saving/loading ORC files without contacting Hive metastore 1. Support for complex data types (i.e. array, map, and struct) 1. Aware of common optimizations provided by Spark SQL: - Column pruning - Partitioning pruning - Filter push-down 1. Schema evolution support 1. Hive metastore table conversion This PR also include initial work done by scwf from Huawei (PR apache#3753). Author: Zhan Zhang <zhazhan@gmail.com> Author: Cheng Lian <lian@databricks.com> Closes apache#6194 from liancheng/polishing-orc and squashes the following commits: 55ecd96 [Cheng Lian] Reorganizes ORC test suites d4afeed [Cheng Lian] Addresses comments 21ada22 [Cheng Lian] Adds @SInCE and @experimental annotations 128bd3b [Cheng Lian] ORC filter bug fix d734496 [Cheng Lian] Polishes the ORC data source 2650a42 [Zhan Zhang] resolve review comments 3c9038e [Zhan Zhang] resolve review comments 7b3c7c5 [Zhan Zhang] save mode fix f95abfd [Zhan Zhang] reuse test suite 7cc2c64 [Zhan Zhang] predicate fix 4e61c16 [Zhan Zhang] minor change 305418c [Zhan Zhang] orc data source support
spark-sql> > explain extended > select * from ( > select key from src union all > select key from src) t; now the spark plan will print children in argString ``` == Physical Plan == Union[ HiveTableScan key#1, (MetastoreRelation default, src, None), None, HiveTableScan key#3, (MetastoreRelation default, src, None), None] HiveTableScan key#1, (MetastoreRelation default, src, None), None HiveTableScan key#3, (MetastoreRelation default, src, None), None ``` after this patch: ``` == Physical Plan == Union HiveTableScan [key#1], (MetastoreRelation default, src, None), None HiveTableScan [key#3], (MetastoreRelation default, src, None), None ``` I have tested this locally Author: scwf <wangfei1@huawei.com> Closes apache#6144 from scwf/fix-argString and squashes the following commits: 1a642e0 [scwf] fix treenode argString
…als) A modified version of apache#6110, use `semanticEquals` to make it more efficient. Author: Wenchen Fan <cloud0fan@outlook.com> Closes apache#6173 from cloud-fan/7269 and squashes the following commits: e4a3cc7 [Wenchen Fan] address comments cc02045 [Wenchen Fan] consider elements length equal d7ff8f4 [Wenchen Fan] fix 7269
… based on mapreduce apis cc liancheng marmbrus Author: Yin Huai <yhuai@databricks.com> Closes apache#6130 from yhuai/directOutput and squashes the following commits: 312b07d [Yin Huai] A data source can use spark.sql.sources.outputCommitterClass to override the output committer.
…ance optimizations
This PR introduces several performance optimizations to `HadoopFsRelation` and `ParquetRelation2`:
1. Moving `FileStatus` listing from `DataSourceStrategy` into a cache within `HadoopFsRelation`.
This new cache generalizes and replaces the one used in `ParquetRelation2`.
This also introduces an interface change: to reuse cached `FileStatus` objects, `HadoopFsRelation.buildScan` methods now receive `Array[FileStatus]` instead of `Array[String]`.
1. When Parquet task side metadata reading is enabled, skip reading row group information when reading Parquet footers.
This is basically what PR apache#5334 does. Also, now we uses `ParquetFileReader.readAllFootersInParallel` to read footers in parallel.
Another optimization in question is, instead of asking `HadoopFsRelation.buildScan` to return an `RDD[Row]` for a single selected partition and then union them all, we ask it to return an `RDD[Row]` for all selected partitions. This optimization is based on the fact that Hadoop configuration broadcasting used in `NewHadoopRDD` takes 34% time in the following microbenchmark. However, this complicates data source user code because user code must merge partition values manually.
To check the cost of broadcasting in `NewHadoopRDD`, I also did microbenchmark after removing the `broadcast` call in `NewHadoopRDD`. All results are shown below.
### Microbenchmark
#### Preparation code
Generating a partitioned table with 50k partitions, 1k rows per partition:
```scala
import sqlContext._
import sqlContext.implicits._
for (n <- 0 until 500) {
val data = for {
p <- (n * 10) until ((n + 1) * 10)
i <- 0 until 1000
} yield (i, f"val_$i%04d", f"$p%04d")
data.
toDF("a", "b", "p").
write.
partitionBy("p").
mode("append").
parquet(path)
}
```
#### Benchmarking code
```scala
import sqlContext._
import sqlContext.implicits._
import org.apache.spark.sql.types._
import com.google.common.base.Stopwatch
val path = "hdfs://localhost:9000/user/lian/5k"
def benchmark(n: Int)(f: => Unit) {
val stopwatch = new Stopwatch()
def run() = {
stopwatch.reset()
stopwatch.start()
f
stopwatch.stop()
stopwatch.elapsedMillis()
}
val records = (0 until n).map(_ => run())
(0 until n).foreach(i => println(s"Round $i: ${records(i)} ms"))
println(s"Average: ${records.sum / n.toDouble} ms")
}
benchmark(3) { read.parquet(path).explain(extended = true) }
```
#### Results
Before:
```
Round 0: 72528 ms
Round 1: 68938 ms
Round 2: 65372 ms
Average: 68946.0 ms
```
After:
```
Round 0: 59499 ms
Round 1: 53645 ms
Round 2: 53844 ms
Round 3: 49093 ms
Round 4: 50555 ms
Average: 53327.2 ms
```
Also removing Hadoop configuration broadcasting:
(Note that I was testing on a local laptop, thus network cost is pretty low.)
```
Round 0: 15806 ms
Round 1: 14394 ms
Round 2: 14699 ms
Round 3: 15334 ms
Round 4: 14123 ms
Average: 14871.2 ms
```
Author: Cheng Lian <lian@databricks.com>
Closes apache#6225 from liancheng/spark-7673 and squashes the following commits:
2d58a2b [Cheng Lian] Skips reading row group information when using task side metadata reading
7aa3748 [Cheng Lian] Optimizes FileStatusCache by introducing a map from parent directories to child files
ba41250 [Cheng Lian] Reuses HadoopFsRelation FileStatusCache in ParquetRelation2
3d278f7 [Cheng Lian] Fixes a bug when reading a single Parquet data file
b84612a [Cheng Lian] Fixes Scala style issue
6a08b02 [Cheng Lian] WIP: Moves file status cache into HadoopFSRelation
This PR revert apache#5404, change to pass the version of python in driver into JVM, check it in worker before deserializing closure, then it can works with different major version of Python. Author: Davies Liu <davies@databricks.com> Closes apache#6203 from davies/py_version and squashes the following commits: b8fb76e [Davies Liu] fix test 6ce5096 [Davies Liu] use string for version 47c6278 [Davies Liu] check python version of worker with driver
…imeline graphs 1. If the user click one point of a batch, scroll down to the corresponding batch row and highlight it. And recovery the batch row after 3 seconds if necessary. 2. Add "#batches" in the histogram graphs.    Author: zsxwing <zsxwing@gmail.com> Closes apache#6168 from zsxwing/SPARK-7658 and squashes the following commits: c242b00 [zsxwing] Change 5 seconds to 3 seconds 31fd0aa [zsxwing] Remove the mouseover highlight feature 06c6f6f [zsxwing] Merge branch 'master' into SPARK-7658 2eaff06 [zsxwing] Merge branch 'master' into SPARK-7658 108d56c [zsxwing] Update the mouse behaviors for the timeline graphs
Fix break caused by merging apache#6225 and apache#6194. Author: Michael Armbrust <michael@databricks.com> Closes apache#6244 from marmbrus/fixOrcBuildBreak and squashes the following commits: b10e47b [Michael Armbrust] [HOTFIX] Fix ORC Build break
This is similar to apache#5999, but for streaming. Roughly 200 lines are tests. One thing to note here is that we already do some kind of scoping thing for call sites, so this patch adds the new RDD operation scoping logic in the same place. Also, this patch adds a `try finally` block to set the relevant variables in a safer way. tdas zsxwing ------------------------ **Before** <img src="https://cloud.githubusercontent.com/assets/2133137/7625996/d88211b8-f9b4-11e4-90b9-e11baa52d6d7.png" width="450px"/> -------------------------- **After** <img src="https://cloud.githubusercontent.com/assets/2133137/7625997/e0878f8c-f9b4-11e4-8df3-7dd611b13c87.png" width="650px"/> Author: Andrew Or <andrew@databricks.com> Closes apache#6034 from andrewor14/dag-viz-streaming and squashes the following commits: 932a64a [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming e685df9 [Andrew Or] Rename createRDDWith 84d0656 [Andrew Or] Review feedback 697c086 [Andrew Or] Fix tests 53b9936 [Andrew Or] Set scopes for foreachRDD properly 1881802 [Andrew Or] Refactor DStream scope names again af4ba8d [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming fd07d22 [Andrew Or] Make MQTT lower case f6de871 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming 0ca1801 [Andrew Or] Remove a few unnecessary withScopes on aliases fa4e5fb [Andrew Or] Pass in input stream name rather than defining it from within 1af0b0e [Andrew Or] Fix style 074c00b [Andrew Or] Review comments d25a324 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming e4a93ac [Andrew Or] Fix tests? 25416dc [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming 9113183 [Andrew Or] Add tests for DStream scopes b3806ab [Andrew Or] Fix test bb80bbb [Andrew Or] Fix MIMA? 5c30360 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming 5703939 [Andrew Or] Rename operations that create InputDStreams 7c4513d [Andrew Or] Group RDDs by DStream operations and batches bf0ab6e [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming 05c2676 [Andrew Or] Wrap many more methods in withScope c121047 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming 65ef3e9 [Andrew Or] Fix NPE a0d3263 [Andrew Or] Scope streaming operations instead of RDD operations
this fix is to solve one issue found in lz4 1.2.0, which caused core dump in Spark Core with IBM JDK. that issue is fixed in lz4 1.3.0 version. Author: Jihong MA <linlin200605@gmail.com> Closes apache#6226 from JihongMA/SPARK-7063-1 and squashes the following commits: 0cca781 [Jihong MA] SPARK-7063 4559ed5 [Jihong MA] SPARK-7063 daa520f [Jihong MA] SPARK-7063 upgrade lz4 jars 71738ee [Jihong MA] Merge remote-tracking branch 'upstream/master' dfaa971 [Jihong MA] SPARK-7265 minor fix of the content ace454d [Jihong MA] SPARK-7265 take out PySpark on YARN limitation 9ea0832 [Jihong MA] Merge remote-tracking branch 'upstream/master' d5bf3f5 [Jihong MA] Merge remote-tracking branch 'upstream/master' 7b842e6 [Jihong MA] Merge remote-tracking branch 'upstream/master' 9c84695 [Jihong MA] SPARK-7265 address review comment a399aa6 [Jihong MA] SPARK-7265 Improving documentation for Spark SQL Hive support
Having a SQLContext singleton would make it easier for applications to use a lazily instantiated single shared instance of SQLContext when needed. It would avoid problems like
1. In REPL/notebook environment, rerunning the line {{val sqlContext = new SQLContext}} multiple times created different contexts while overriding the reference to previous context, leading to issues like registered temp tables going missing.
2. In Streaming, creating SQLContext directly leads to serialization/deserialization issues when attempting to recover from DStream checkpoints. See [SPARK-6770]. Also to get around this problem I had to suggest creating a singleton instance - https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala
This can be solved by {{SQLContext.getOrCreate}} which get or creates a new singleton instance of SQLContext using either a given SparkContext or a given SparkConf.
rxin marmbrus
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes apache#6006 from tdas/SPARK-7478 and squashes the following commits:
25f4da9 [Tathagata Das] Addressed comments.
79fe069 [Tathagata Das] Added comments.
c66ca76 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-7478
48adb14 [Tathagata Das] Removed HiveContext.getOrCreate
bf8cf50 [Tathagata Das] Fix more bug
dec5594 [Tathagata Das] Fixed bug
b4e9721 [Tathagata Das] Remove unnecessary import
4ef513b [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-7478
d3ea8e4 [Tathagata Das] Added HiveContext
83bc950 [Tathagata Das] Updated tests
f82ae81 [Tathagata Das] Fixed test
bc72868 [Tathagata Das] Added SQLContext.getOrCreate
…in Scala Author: Holden Karau <holden@pigscanfly.ca> Closes apache#6275 from holdenk/SPARK-771-startTime-is-missing-from-pyspark and squashes the following commits: 06662dc [Holden Karau] add mising blank line for style checks 7a87410 [Holden Karau] add back missing newline 7a7876b [Holden Karau] Add a startTime property to match the corresponding one in the Scala SparkContext
According to yhuai we spent 6-7 seconds cleaning closures in a partitioning job that takes 12 seconds. Since we provide these closures in Spark we know for sure they are serializable, so we can bypass the cleaning. Author: Andrew Or <andrew@databricks.com> Closes apache#6256 from andrewor14/sql-partition-speed-up and squashes the following commits: a82b451 [Andrew Or] Fix style 10f7e3e [Andrew Or] Avoid getting call sites and cleaning closures 17e2943 [Andrew Or] Merge branch 'master' of github.com:apache/spark into sql-partition-speed-up 523f042 [Andrew Or] Skip unnecessary Utils.getCallSites too f7fe143 [Andrew Or] Avoid unnecessary closure cleaning
JIRA: https://issues.apache.org/jira/browse/SPARK-7800 `isDefined` is marked as true twice in `Location.putNewKey`. The first one is unnecessary and will cause problem because it is too early and before some assert checking. E.g., if an attempt with incorrect `keyLengthBytes` marks `isDefined` as true, the location can not be used later. ping JoshRosen Author: Liang-Chi Hsieh <viirya@gmail.com> Closes apache#6324 from viirya/dup_isdefined and squashes the following commits: cbfe03b [Liang-Chi Hsieh] isDefined should not marked too early in putNewKey.
Seems our master build does not run HiveCompatibilitySuite (because _RUN_SQL_TESTS is not set). This PR introduces a property `AMP_JENKINS_PRB` to differentiate a PR build and a regular build. If a build is a regular one, we always set _RUN_SQL_TESTS to true. cc JoshRosen nchammas Author: Yin Huai <yhuai@databricks.com> Closes apache#5955 from yhuai/runSQLTests and squashes the following commits: 3d399bc [Yin Huai] Always run SQL tests in master build.
…ions. https://issues.apache.org/jira/browse/SPARK-7737 cc liancheng Author: Yin Huai <yhuai@databricks.com> Closes apache#6329 from yhuai/spark-7737 and squashes the following commits: 7e0dfc7 [Yin Huai] Use leaf dirs having data files to discover partitions.
Shutdown hook to stop SparkContext was added recently. This results in ugly errors when a streaming application is terminated by ctrl-C. ``` Exception in thread "Thread-27" org.apache.spark.SparkException: Job cancelled because SparkContext was shut down at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:736) at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:735) at scala.collection.mutable.HashSet.foreach(HashSet.scala:79) at org.apache.spark.scheduler.DAGScheduler.cleanUpAfterSchedulerStop(DAGScheduler.scala:735) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onStop(DAGScheduler.scala:1468) at org.apache.spark.util.EventLoop.stop(EventLoop.scala:84) at org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:1403) at org.apache.spark.SparkContext.stop(SparkContext.scala:1642) at org.apache.spark.SparkContext$$anonfun$3.apply$mcV$sp(SparkContext.scala:559) at org.apache.spark.util.SparkShutdownHook.run(Utils.scala:2266) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(Utils.scala:2236) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(Utils.scala:2236) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(Utils.scala:2236) at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1764) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply$mcV$sp(Utils.scala:2236) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(Utils.scala:2236) at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(Utils.scala:2236) at scala.util.Try$.apply(Try.scala:161) at org.apache.spark.util.SparkShutdownHookManager.runAll(Utils.scala:2236) at org.apache.spark.util.SparkShutdownHookManager$$anon$6.run(Utils.scala:2218) at org.apache.hadoop.util.ShutdownHookManager$1.run(ShutdownHookManager.java:54) ``` This is because the Spark's shutdown hook stops the context, and the streaming jobs fail in the middle. The correct solution is to stop the streaming context before the spark context. This PR adds the shutdown hook to do so with a priority higher than the SparkContext's shutdown hooks priority. Author: Tathagata Das <tathagata.das1565@gmail.com> Closes apache#6307 from tdas/SPARK-7776 and squashes the following commits: e3d5475 [Tathagata Das] Added conf to specify graceful shutdown 4c18652 [Tathagata Das] Added shutdown hook to StreamingContxt.
Author: Davies Liu <davies@databricks.com> Closes apache#6311 from davies/rollup and squashes the following commits: 0261db1 [Davies Liu] use @SInCE a51ca6b [Davies Liu] Merge branch 'master' of github.com:apache/spark into rollup 8ad5af4 [Davies Liu] Update dataframe.py ade3841 [Davies Liu] add DataFrame.rollup/cube in Python
The previous default is `{gaps: false, pattern: "\\p{L}+|[^\\p{L}\\s]+"}`. The default pattern is hard to understand. This PR changes the default to `{gaps: true, pattern: "\\s+"}`. jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes apache#6330 from mengxr/SPARK-7794 and squashes the following commits:
5ee7cde [Xiangrui Meng] update RegexTokenizer default settings
This PR updates `HashingTF` to output ML attributes that tell the number of features in the output column. We need to expand `UnaryTransformer` to support output metadata. A `df outputMetadata: Metadata` is not sufficient because the metadata may also depends on the input data. Though this is not true for `HashingTF`, I think it is reasonable to update `UnaryTransformer` in a separate PR. `checkParams` is added to verify common requirements for params. I will send a separate PR to use it in other test suites. jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes apache#6308 from mengxr/SPARK-7219 and squashes the following commits: 9bd2922 [Xiangrui Meng] address comments e82a68a [Xiangrui Meng] remove sqlContext from test suite 995535b [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-7219 2194703 [Xiangrui Meng] add test for attributes 178ae23 [Xiangrui Meng] update HashingTF with tests 91a6106 [Xiangrui Meng] WIP
…er mode. This PR adds the URLs to the driver logs to `SparkListenerApplicationStarted` event, which is later used by the `ExecutorsListener` to populate the URLs to the driver logs in its own state. This info is then used when the UI is rendered to display links to the logs. Author: Hari Shreedharan <hshreedharan@apache.org> Closes apache#6166 from harishreedharan/am-log-link and squashes the following commits: 943fc4f [Hari Shreedharan] Merge remote-tracking branch 'asf/master' into am-log-link 9e5c04b [Hari Shreedharan] Merge remote-tracking branch 'asf/master' into am-log-link b3f9b9d [Hari Shreedharan] Updated comment based on feedback. 0840a95 [Hari Shreedharan] Move the result and sc.stop back to original location, minor import changes. 537a2f7 [Hari Shreedharan] Add test to ensure the log urls are populated and valid. 4033725 [Hari Shreedharan] Adding comments explaining how node reports are used to get the log urls. 6c5c285 [Hari Shreedharan] Import order. 346f4ea [Hari Shreedharan] Review feedback fixes. 629c1dc [Hari Shreedharan] Cleanup. 99fb1a3 [Hari Shreedharan] Send the log urls in App start event, to ensure that other listeners are not affected. c0de336 [Hari Shreedharan] Ensure new unit test cleans up after itself. 50cdae3 [Hari Shreedharan] Added unit test, made the approach generic. 402e8e4 [Hari Shreedharan] Use `NodeReport` to get the URL for the logs. Also, make the environment variables generic so other cluster managers can use them as well. 1cf338f [Hari Shreedharan] [SPARK-7657][YARN] Add driver link in application UI, in cluster mode.
Just a small change: fixed a broken link in the MLlib Linear Methods documentation by removing a newline character between the link title and link address. Author: Mike Dusenberry <dusenberrymw@gmail.com> Closes apache#6340 from dusenberrymw/Fix_MLlib_Linear_Methods_link and squashes the following commits: 0a57818 [Mike Dusenberry] Fixing broken link in MLlib Linear Methods documentation.
Some changes to the pipeilne APIs: 1. Estimator/Transformer/ doesn’t need to extend Params since PipelineStage already does. 1. Move Evaluator to ml.evaluation. 1. Mention larger metric values are better. 1. PipelineModel doc. “compiled” -> “fitted” 1. Hide object PolynomialExpansion. 1. Hide object VectorAssembler. 1. Word2Vec.minCount (and other) -> group param 1. ParamValidators -> DeveloperApi 1. Hide MetadataUtils/SchemaUtils. jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes apache#6322 from mengxr/SPARK-7535.0 and squashes the following commits: 9e9c7da [Xiangrui Meng] move JavaEvaluator to ml.evaluation as well e179480 [Xiangrui Meng] move Evaluation to ml.evaluation in PySpark 08ef61f [Xiangrui Meng] update pipieline APIs
…dardScaler Added user guide sections with code examples. Also added small Java unit tests to test Java example in guide. CC: mengxr Author: Joseph K. Bradley <joseph@databricks.com> Closes apache#6127 from jkbradley/feature-guide-2 and squashes the following commits: cd47f4b [Joseph K. Bradley] Updated based on code review f16bcec [Joseph K. Bradley] Fixed merge issues and update Python examples print calls for Python 3 0a862f9 [Joseph K. Bradley] Added Normalizer, StandardScaler to ml-features doc, plus small Java unit tests a21c2d6 [Joseph K. Bradley] Updated ml-features.md with IDF
This closes apache#6104. Author: Cheng Hao <hao.cheng@intel.com> Author: Reynold Xin <rxin@databricks.com> Closes apache#6343 from rxin/window-df and squashes the following commits: 026d587 [Reynold Xin] Address code review feedback. dc448fe [Reynold Xin] Fixed Hive tests. 9794d9d [Reynold Xin] Moved Java test package. 9331605 [Reynold Xin] Refactored API. 3313e2a [Reynold Xin] Merge pull request apache#6104 from chenghao-intel/df_window d625a64 [Cheng Hao] Update the dataframe window API as suggsted c141fb1 [Cheng Hao] hide all of properties of the WindowFunctionDefinition 3b1865f [Cheng Hao] scaladoc typos f3fd2d0 [Cheng Hao] polish the unit test 6847825 [Cheng Hao] Add additional analystcs functions 57e3bc0 [Cheng Hao] typos 24a08ec [Cheng Hao] scaladoc 28222ed [Cheng Hao] fix bug of range/row Frame 1d91865 [Cheng Hao] style issue 53f89f2 [Cheng Hao] remove the over from the functions.scala 964c013 [Cheng Hao] add more unit tests and window functions 64e18a7 [Cheng Hao] Add Window Function support for DataFrame
This Selenium test case has been flaky for a while and led to frequent Jenkins build failure. Let's disable it temporarily until we figure out a proper solution. Author: Cheng Lian <lian@databricks.com> Closes apache#6345 from liancheng/ignore-selenium-test and squashes the following commits: 09996fe [Cheng Lian] Ignores Thrift server UISeleniumSuite
Author: Michael Armbrust <michael@databricks.com> Closes apache#6165 from marmbrus/wrongColumn and squashes the following commits: 4fad158 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into wrongColumn aad7eab [Michael Armbrust] rxins comments f1e8df1 [Michael Armbrust] [SPARK-6743][SQL] Fix empty projections of cached data
Author: Ram Sriharsha <rsriharsha@hw11853.local> Closes apache#6344 from harsha2010/SPARK-7404 and squashes the following commits: 16b9d77 [Ram Sriharsha] consistent naming 7f100b6 [Ram Sriharsha] cleanup c46044d [Ram Sriharsha] Merge with Master + Code Review Fixes 188fa0a [Ram Sriharsha] Merge branch 'master' into SPARK-7404 f5b6a4c [Ram Sriharsha] cleanup doc 97beca5 [Ram Sriharsha] update test to use R packages 32dd310 [Ram Sriharsha] fix indentation f93b812 [Ram Sriharsha] fix test 1b6ebb3 [Ram Sriharsha] [SPARK-7404][ml] Add RegressionEvaluator to spark.ml
This reverts commit 147b6be.
Including Iris Dataset (after shuffling and relabeling 3 -> 0 to confirm to 0 -> numClasses-1 labeling). Could not find an existing dataset in data/mllib for multiclass classification. Author: Ram Sriharsha <rsriharsha@hw11853.local> Closes apache#6296 from harsha2010/SPARK-7574 and squashes the following commits: 645427c [Ram Sriharsha] cleanup 46c41b1 [Ram Sriharsha] cleanup 2f76295 [Ram Sriharsha] Code Review Fixes ebdf103 [Ram Sriharsha] Java Example c026613 [Ram Sriharsha] Code Review fixes 4b7d1a6 [Ram Sriharsha] minor cleanup 13bed9c [Ram Sriharsha] add wikipedia link bb9dbfa [Ram Sriharsha] Clean up naming 6f90db1 [Ram Sriharsha] [SPARK-7574][ml][doc] User guide for OneVsRest
…s disabled SPARK-3386 / apache#5606 modified the shuffle write path to re-use serializer instances across multiple calls to DiskBlockObjectWriter. It turns out that this introduced a very rare bug when using `KryoSerializer`: if auto-reset is disabled and reference-tracking is enabled, then we'll end up re-using the same serializer instance to write multiple output streams without calling `reset()` between write calls, which can lead to cases where objects in one file may contain references to objects that are in previous files, causing errors during deserialization. This patch fixes this bug by calling `reset()` at the start of `serialize()` and `serializeStream()`. I also added a regression test which demonstrates that this problem only occurs when auto-reset is disabled and reference-tracking is enabled. Author: Josh Rosen <joshrosen@databricks.com> Closes apache#6293 from JoshRosen/kryo-instance-reuse-bug and squashes the following commits: e19726d [Josh Rosen] Add fix for SPARK-7766. 71845e3 [Josh Rosen] Add failing regression test to trigger Kryo re-use bug
…t to a postgre sql https://issues.apache.org/jira/browse/SPARK-7758 When initializing `executionHive`, we only masks `javax.jdo.option.ConnectionURL` to override metastore location. However, other properties that relates to the actual Hive metastore data source are not masked. For example, when using Spark SQL with a PostgreSQL backed Hive metastore, `executionHive` actually tries to use settings read from `hive-site.xml`, which talks about PostgreSQL, to connect to the temporary Derby metastore, thus causes error. To fix this, we need to mask all metastore data source properties. Specifically, according to the code of [Hive `ObjectStore.getDataSourceProps()` method] [1], all properties whose name mentions "jdo" and "datanucleus" must be included. [1]: https://github.com/apache/hive/blob/release-0.13.1/metastore/src/java/org/apache/hadoop/hive/metastore/ObjectStore.java#L288 Have tested using postgre sql as metastore, it worked fine. Author: WangTaoTheTonic <wangtao111@huawei.com> Closes apache#6314 from WangTaoTheTonic/SPARK-7758 and squashes the following commits: ca7ae7c [WangTaoTheTonic] add comments 86caf2c [WangTaoTheTonic] delete unused import e4f0feb [WangTaoTheTonic] block more data source related property 92a81fa [WangTaoTheTonic] fix style check e3e683d [WangTaoTheTonic] override more configs to avoid failuer connecting to postgre sql
Author: Santiago M. Mola <santi@mola.io> Closes apache#6327 from smola/feature/catalyst-dsl-set-ops and squashes the following commits: 11db778 [Santiago M. Mola] [SPARK-7724] [SQL] Support Intersect/Except in Catalyst DSL.
…e table JIRA: https://issues.apache.org/jira/browse/SPARK-7270 Author: Liang-Chi Hsieh <viirya@gmail.com> Closes apache#5864 from viirya/dyn_partition_insert and squashes the following commits: b5627df [Liang-Chi Hsieh] For comments. 3b21e4b [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into dyn_partition_insert 8a4352d [Liang-Chi Hsieh] Consider dynamic partition when inserting into hive table.
…ertIntoHadoopFsRelation.
rxin
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## What changes were proposed in this pull request?
This PR brings the support for chained Python UDFs, for example
```sql
select udf1(udf2(a))
select udf1(udf2(a) + 3)
select udf1(udf2(a) + udf3(b))
```
Also directly chained unary Python UDFs are put in single batch of Python UDFs, others may require multiple batches.
For example,
```python
>>> sqlContext.sql("select double(double(1))").explain()
== Physical Plan ==
WholeStageCodegen
: +- Project [pythonUDF#10 AS double(double(1))#9]
: +- INPUT
+- !BatchPythonEvaluation double(double(1)), [pythonUDF#10]
+- Scan OneRowRelation[]
>>> sqlContext.sql("select double(double(1) + double(2))").explain()
== Physical Plan ==
WholeStageCodegen
: +- Project [pythonUDF#19 AS double((double(1) + double(2)))#16]
: +- INPUT
+- !BatchPythonEvaluation double((pythonUDF#17 + pythonUDF#18)), [pythonUDF#17,pythonUDF#18,pythonUDF#19]
+- !BatchPythonEvaluation double(2), [pythonUDF#17,pythonUDF#18]
+- !BatchPythonEvaluation double(1), [pythonUDF#17]
+- Scan OneRowRelation[]
```
TODO: will support multiple unrelated Python UDFs in one batch (another PR).
## How was this patch tested?
Added new unit tests for chained UDFs.
Author: Davies Liu <davies@databricks.com>
Closes apache#12014 from davies/py_udfs.
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