Wrong request, please ignore. #8443
Closed
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
`RuleExecutor.timeMap` is currently a non-thread-safe mutable HashMap; this can lead to infinite loops if multiple threads are concurrently modifying the map. I believe that this is responsible for some hangs that I've observed in HiveQuerySuite. This patch addresses this by using a Guava `AtomicLongMap`. Author: Josh Rosen <joshrosen@databricks.com> Closes #8120 from JoshRosen/rule-executor-time-map-fix.
Author: xutingjun <xutingjun@huawei.com> Author: meiyoula <1039320815@qq.com> Closes #6817 from XuTingjun/SPARK-8366.
…applications Author: Rohit Agarwal <rohita@qubole.com> Closes #8088 from mindprince/SPARK-9806.
The peak execution memory is not correct because it shows the sum of finished tasks' values when a task finishes. This PR fixes it by using the update value rather than the accumulator value. Author: zsxwing <zsxwing@gmail.com> Closes #8121 from zsxwing/SPARK-9829.
To reproduce the issue, go to the stage page and click DAG Visualization once, then go to the job page to show the job DAG visualization. You will only see the first stage of the job. Root cause: the java script use local storage to remember your selection. Once you click the stage DAG visualization, the local storage set `expand-dag-viz-arrow-stage` to true. When you go to the job page, the js checks `expand-dag-viz-arrow-stage` in the local storage first and will try to show stage DAG visualization on the job page. To fix this, I set an id to the DAG span to differ job page and stage page. In the js code, we check the id and local storage together to make sure we show the correct DAG visualization. Author: Carson Wang <carson.wang@intel.com> Closes #8104 from carsonwang/SPARK-9426.
Some users like to download additional files in their sandbox that they can refer to from their spark program, or even later mount these files to another directory. Author: Timothy Chen <tnachen@gmail.com> Closes #7195 from tnachen/mesos_files.
andrewor14 Author: Timothy Chen <tnachen@gmail.com> Closes #7907 from tnachen/mesos_shuffle.
This PR fixes unable to push filter down to JDBC source caused by `Cast` during pattern matching. While we are comparing columns of different type, there's a big chance we need a cast on the column, therefore not match the pattern directly on Attribute and would fail to push down. Author: Yijie Shen <henry.yijieshen@gmail.com> Closes #8049 from yjshen/jdbc_pushdown.
…tes to be pushed down This PR adds a hacky workaround for PARQUET-201, and should be removed once we upgrade to parquet-mr 1.8.1 or higher versions. In Parquet, not all types of columns can be used for filter push-down optimization. The set of valid column types is controlled by `ValidTypeMap`. Unfortunately, in parquet-mr 1.7.0 and prior versions, this limitation is too strict, and doesn't allow `BINARY (ENUM)` columns to be pushed down. On the other hand, `BINARY (ENUM)` is commonly seen in Parquet files written by libraries like `parquet-avro`. This restriction is problematic for Spark SQL, because Spark SQL doesn't have a type that maps to Parquet `BINARY (ENUM)` directly, and always converts `BINARY (ENUM)` to Catalyst `StringType`. Thus, a predicate involving a `BINARY (ENUM)` is recognized as one involving a string field instead and can be pushed down by the query optimizer. Such predicates are actually perfectly legal except that it fails the `ValidTypeMap` check. The workaround added here is relaxing `ValidTypeMap` to include `BINARY (ENUM)`. I also took the chance to simplify `ParquetCompatibilityTest` a little bit when adding regression test. Author: Cheng Lian <lian@databricks.com> Closes #8107 from liancheng/spark-9407/parquet-enum-filter-push-down.
This allows clients to retrieve the original exception from the cause field of the SparkException that is thrown by the driver. If the original exception is not in fact Serializable then it will not be returned, but the message and stacktrace will be. (All Java Throwables implement the Serializable interface, but this is no guarantee that a particular implementation can actually be serialized.) Author: Tom White <tom@cloudera.com> Closes #7014 from tomwhite/propagate-user-exceptions.
…ame executor twice This is based on KaiXinXiaoLei's changes in #7716. The issue is that when someone calls `sc.killExecutor("1")` on the same executor twice quickly, then the executor target will be adjusted downwards by 2 instead of 1 even though we're only actually killing one executor. In certain cases where we don't adjust the target back upwards quickly, we'll end up with jobs hanging. This is a common danger because there are many places where this is called: - `HeartbeatReceiver` kills an executor that has not been sending heartbeats - `ExecutorAllocationManager` kills an executor that has been idle - The user code might call this, which may interfere with the previous callers While it's not clear whether this fixes SPARK-9745, fixing this potential race condition seems like a strict improvement. I've added a regression test to illustrate the issue. Author: Andrew Or <andrew@databricks.com> Closes #8078 from andrewor14/da-double-kill.
jira: https://issues.apache.org/jira/browse/SPARK-7583 User guide update for RegexTokenizer Author: Yuhao Yang <hhbyyh@gmail.com> Closes #7828 from hhbyyh/regexTokenizerDoc.
This is the sister patch to #8011, but for aggregation. In a nutshell: create the `TungstenAggregationIterator` before computing the parent partition. Internally this creates a `BytesToBytesMap` which acquires a page in the constructor as of this patch. This ensures that the aggregation operator is not starved since we reserve at least 1 page in advance. rxin yhuai Author: Andrew Or <andrew@databricks.com> Closes #8038 from andrewor14/unsafe-starve-memory-agg.
If the correct parameter is not provided, Hive will run into an error because it calls methods that are specific to the local filesystem to copy the data. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #8086 from vanzin/SPARK-9804.
… explicit param values From JIRA: Currently, Params.copyValues copies default parameter values to the paramMap of the target instance, rather than the defaultParamMap. It should copy to the defaultParamMap because explicitly setting a parameter can change the semantics. This issue arose in SPARK-9789, where 2 params "threshold" and "thresholds" for LogisticRegression can have mutually exclusive values. If thresholds is set, then fit() will copy the default value of threshold as well, easily resulting in inconsistent settings for the 2 params. CC: mengxr Author: Joseph K. Bradley <joseph@databricks.com> Closes #8115 from jkbradley/copyvalues-fix.
rxin First pull request for Spark so let me know if I am missing anything The contribution is my original work and I license the work to the project under the project's open source license. Author: Brennan Ashton <bashton@brennanashton.com> Closes #8016 from btashton/patch-1.
Check and add miss docs for PySpark ML (this issue only check miss docs for o.a.s.ml not o.a.s.mllib). Author: Yanbo Liang <ybliang8@gmail.com> Closes #8059 from yanboliang/SPARK-9766.
Reinstated LogisticRegression.threshold Param for binary compatibility. Param thresholds overrides threshold, if set. CC: mengxr dbtsai feynmanliang Author: Joseph K. Bradley <joseph@databricks.com> Closes #8079 from jkbradley/logreg-reinstate-threshold.
Add `Since` as a Scala annotation. The benefit is that we can use it without having explicit JavaDoc. This is useful for inherited methods. The limitation is that is doesn't show up in the generated Java API documentation. This might be fixed by modifying genjavadoc. I think we could leave it as a TODO. This is how the generated Scala doc looks: `since` JavaDoc tag:  `Since` annotation:  rxin Author: Xiangrui Meng <meng@databricks.com> Closes #8131 from mengxr/SPARK-8967.
Author: Reynold Xin <rxin@databricks.com> Closes #8138 from rxin/SPARK-9907.
…c... … allocation are set. Now, dynamic allocation is set to false when num-executors is explicitly specified as an argument. Consequently, executorAllocationManager in not initialized in the SparkContext. Author: Niranjan Padmanabhan <niranjan.padmanabhan@cloudera.com> Closes #7657 from neurons/SPARK-9092.
Refactor Utils class and create ShutdownHookManager.
NOTE: Wasn't able to run /dev/run-tests on windows machine.
Manual tests were conducted locally using custom log4j.properties file with Redis appender and logstash formatter (bundled in the fat-jar submitted to spark)
ex:
log4j.rootCategory=WARN,console,redis
log4j.appender.console=org.apache.log4j.ConsoleAppender
log4j.appender.console.target=System.err
log4j.appender.console.layout=org.apache.log4j.PatternLayout
log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n
log4j.logger.org.eclipse.jetty=WARN
log4j.logger.org.eclipse.jetty.util.component.AbstractLifeCycle=ERROR
log4j.logger.org.apache.spark.repl.SparkIMain$exprTyper=INFO
log4j.logger.org.apache.spark.repl.SparkILoop$SparkILoopInterpreter=INFO
log4j.logger.org.apache.spark.graphx.Pregel=INFO
log4j.appender.redis=com.ryantenney.log4j.FailoverRedisAppender
log4j.appender.redis.endpoints=hostname:port
log4j.appender.redis.key=mykey
log4j.appender.redis.alwaysBatch=false
log4j.appender.redis.layout=net.logstash.log4j.JSONEventLayoutV1
Author: michellemay <mlemay@gmail.com>
Closes #8109 from michellemay/SPARK-9826.
https://issues.apache.org/jira/browse/SPARK-9894 Author: Yin Huai <yhuai@databricks.com> Closes #8137 from yhuai/jsonMapData.
feynmanliang Author: Xiangrui Meng <meng@databricks.com> Closes #8142 from mengxr/SPARK-9913.
As per the TODO move weightCol to Shared Params. Author: Holden Karau <holden@pigscanfly.ca> Closes #8144 from holdenk/SPARK-9909-move-weightCol-toSharedParams.
…ype names instead of UType and VType hhbyyh Author: Xiangrui Meng <meng@databricks.com> Closes #8140 from mengxr/SPARK-9912.
hhbyyh Author: Xiangrui Meng <meng@databricks.com> Closes #8141 from mengxr/SPARK-9915.
Author: Michael Armbrust <michael@databricks.com> Closes #8119 from marmbrus/metastoreInputFiles.
…fails Author: cody koeninger <cody@koeninger.org> Closes #8133 from koeninger/SPARK-9780 and squashes the following commits: 406259d [cody koeninger] [SPARK-9780][Streaming][Kafka] prevent NPE if KafkaRDD instantiation fails
Author: Rohit Agarwal <rohita@qubole.com> Closes #8014 from mindprince/SPARK-9724 and squashes the following commits: a7af5ff [Rohit Agarwal] [SPARK-9724] [WEB UI] Inline attachPrefix and attachPrefixForRedirect. Fix logic of attachPrefix 8a977cd [Rohit Agarwal] [SPARK-9724] [WEB UI] Address review comments: Remove unneeded code, update scaladoc. b257844 [Rohit Agarwal] [SPARK-9724] [WEB UI] Avoid unnecessary redirects in the Spark Web UI.
Spark SQL's data sources API exposes Catalyst's internal types through its Filter interfaces. This is a problem because types like UTF8String are not stable developer APIs and should not be exposed to third-parties. This issue caused incompatibilities when upgrading our `spark-redshift` library to work against Spark 1.5.0. To avoid these issues in the future we should only expose public types through these Filter objects. This patch accomplishes this by using CatalystTypeConverters to add the appropriate conversions. Author: Josh Rosen <joshrosen@databricks.com> Closes #8403 from JoshRosen/datasources-internal-vs-external-types.
…rs). https://issues.apache.org/jira/browse/SPARK-10197 Author: Yin Huai <yhuai@databricks.com> Closes #8407 from yhuai/ORCSPARK-10197.
Author: Zhang, Liye <liye.zhang@intel.com> Closes #8412 from liyezhang556520/minorDoc.
Author: ehnalis <zoltan.zvara@gmail.com> Closes #8308 from ehnalis/master.
…ng uses to JavaConverters Replace `JavaConversions` implicits with `JavaConverters` Most occurrences I've seen so far are necessary conversions; a few have been avoidable. None are in critical code as far as I see, yet. Author: Sean Owen <sowen@cloudera.com> Closes #8033 from srowen/SPARK-9613.
Author: Michael Armbrust <michael@databricks.com> Closes #8404 from marmbrus/turnOffPartitionVerification.
jira: https://issues.apache.org/jira/browse/SPARK-8531 Update ML user guide for MinMaxScaler Author: Yuhao Yang <hhbyyh@gmail.com> Author: unknown <yuhaoyan@yuhaoyan-MOBL1.ccr.corp.intel.com> Closes #7211 from hhbyyh/minmaxdoc.
See [discussion](#8254 (comment)) CC jkbradley Author: Feynman Liang <fliang@databricks.com> Closes #8422 from feynmanliang/SPARK-10230.
Update `Since` annotation in `mllib.classification`: 1. add version to classes, objects, constructors, and public variables declared in constructors 2. correct some versions 3. remove `Since` on `toString` MechCoder dbtsai Author: Xiangrui Meng <meng@databricks.com> Closes #8421 from mengxr/SPARK-10231 and squashes the following commits: b2dce80 [Xiangrui Meng] update @SInCE annotation for mllib.classification
This PR: 1. supports transferring arbitrary nested array from JVM to R side in SerDe; 2. based on 1, collect() implemenation is improved. Now it can support collecting data of complex types from a DataFrame. Author: Sun Rui <rui.sun@intel.com> Closes #8276 from sun-rui/SPARK-10048.
* Adds doc for alias of runMIniBatchSGD documenting default value for convergeTol * Cleans up a note in code Author: Feynman Liang <fliang@databricks.com> Closes #8425 from feynmanliang/SPARK-9800.
Same as #8421 but for `mllib.fpm`. cc feynmanliang Author: Xiangrui Meng <meng@databricks.com> Closes #8429 from mengxr/SPARK-10237.
…genceTol default value Adds default convergence tolerance (0.001, set in `GradientDescent.convergenceTol`) to `setConvergenceTol`'s scaladoc Author: Feynman Liang <fliang@databricks.com> Closes #8424 from feynmanliang/SPARK-9797.
…ml and mllib.util Same as #8421 but for `mllib.pmml` and `mllib.util`. cc dbtsai Author: Xiangrui Meng <meng@databricks.com> Closes #8430 from mengxr/SPARK-10239 and squashes the following commits: a189acf [Xiangrui Meng] update since versions in mllib.pmml and mllib.util
In BigDecimal or java.math.BigDecimal, the precision could be smaller than scale, for example, BigDecimal("0.001") has precision = 1 and scale = 3. But DecimalType require that the precision should be larger than scale, so we should use the maximum of precision and scale when inferring the schema from decimal literal.
Author: Davies Liu <davies@databricks.com>
Closes #8428 from davies/smaller_decimal.
Follow the rule in Hive for decimal division. see https://github.com/apache/hive/blob/ac755ebe26361a4647d53db2a28500f71697b276/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDFOPDivide.java#L113 cc chenghao-intel Author: Davies Liu <davies@databricks.com> Closes #8415 from davies/decimal_div2.
* Adds two new sections to LDA's user guide; one for each optimizer/model * Documents new features added to LDA (e.g. topXXXperXXX, asymmetric priors, hyperpam optimization) * Cleans up a TODO and sets a default parameter in LDA code jkbradley hhbyyh Author: Feynman Liang <fliang@databricks.com> Closes #8254 from feynmanliang/SPARK-9888.
Same as #8421 but for `mllib.evaluation`. cc avulanov Author: Xiangrui Meng <meng@databricks.com> Closes #8423 from mengxr/SPARK-10233.
ffchenAtCloudera
changed the title
|
Can one of the admins verify this patch? |
Contributor
|
Could you please close this pull request? We don't have permission to do so. |
Same as #8421 but for `mllib.linalg`. cc dbtsai Author: Xiangrui Meng <meng@databricks.com> Closes #8440 from mengxr/SPARK-10238 and squashes the following commits: b38437e [Xiangrui Meng] update since versions in mllib.linalg
…ndom and mllib.stat The same as #8241 but for `mllib.stat` and `mllib.random`. cc feynmanliang Author: Xiangrui Meng <meng@databricks.com> Closes #8439 from mengxr/SPARK-10242.
Same as #8421 but for `mllib.clustering`. cc feynmanliang yu-iskw Author: Xiangrui Meng <meng@databricks.com> Closes #8435 from mengxr/SPARK-10234.
Same as #8421 but for `mllib.tree`. cc jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes #8442 from mengxr/SPARK-10236.
Same as #8421 but for `mllib.regression`. cc freeman-lab dbtsai Author: Xiangrui Meng <meng@databricks.com> Closes #8426 from mengxr/SPARK-10235 and squashes the following commits: 6cd28e4 [Xiangrui Meng] update since versions in mllib.regression
Same as #8421 but for `mllib.feature`. cc dbtsai Author: Xiangrui Meng <meng@databricks.com> Closes #8449 from mengxr/SPARK-10236.feature and squashes the following commits: 0e8d658 [Xiangrui Meng] remove unnecessary comment ad70b03 [Xiangrui Meng] update since versions in mllib.feature
…r filter / select) Add support for ``` df[df$name == "Smith", c(1,2)] df[df$age %in% c(19, 30), 1:2] ``` shivaram Author: felixcheung <felixcheung_m@hotmail.com> Closes #8394 from felixcheung/rsubset.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
20 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
No description provided.