[SPARK-17445][DOCS] Reference an ASF page as the main place to find third-party packages
## What changes were proposed in this pull request? Point references to spark-packages.org to https://cwiki.apache.org/confluence/display/SPARK/Third+Party+Projects This will be accompanied by a parallel change to the spark-website repo, and additional changes to this wiki. ## How was this patch tested? Jenkins tests. Author: Sean Owen <sowen@cloudera.com> Closes #15075 from srowen/SPARK-17445.
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Sean Owen
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@ -6,7 +6,7 @@ It lists steps that are required before creating a PR. In particular, consider:
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- Is the change important and ready enough to ask the community to spend time reviewing?
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- Have you searched for existing, related JIRAs and pull requests?
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- Is this a new feature that can stand alone as a package on http://spark-packages.org ?
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- Is this a new feature that can stand alone as a [third party project](https://cwiki.apache.org/confluence/display/SPARK/Third+Party+Projects) ?
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- Is the change being proposed clearly explained and motivated?
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When you contribute code, you affirm that the contribution is your original work and that you
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@ -100,7 +100,7 @@ sparkR.stop <- function() {
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#' @param sparkEnvir Named list of environment variables to set on worker nodes
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#' @param sparkExecutorEnv Named list of environment variables to be used when launching executors
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#' @param sparkJars Character vector of jar files to pass to the worker nodes
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#' @param sparkPackages Character vector of packages from spark-packages.org
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#' @param sparkPackages Character vector of package coordinates
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#' @seealso \link{sparkR.session}
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#' @rdname sparkR.init-deprecated
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#' @export
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@ -327,7 +327,7 @@ sparkRHive.init <- function(jsc = NULL) {
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#' @param sparkHome Spark Home directory.
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#' @param sparkConfig named list of Spark configuration to set on worker nodes.
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#' @param sparkJars character vector of jar files to pass to the worker nodes.
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#' @param sparkPackages character vector of packages from spark-packages.org
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#' @param sparkPackages character vector of package coordinates
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#' @param enableHiveSupport enable support for Hive, fallback if not built with Hive support; once
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#' set, this cannot be turned off on an existing session
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#' @param ... named Spark properties passed to the method.
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@ -114,7 +114,7 @@
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<li class="divider"></li>
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<li><a href="building-spark.html">Building Spark</a></li>
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<li><a href="https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark">Contributing to Spark</a></li>
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<li><a href="https://cwiki.apache.org/confluence/display/SPARK/Supplemental+Spark+Projects">Supplemental Projects</a></li>
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<li><a href="https://cwiki.apache.org/confluence/display/SPARK/Third+Party+Projects">Third Party Projects</a></li>
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</ul>
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</li>
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</ul>
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@ -120,7 +120,7 @@ options for deployment:
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* [OpenStack Swift](storage-openstack-swift.html)
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* [Building Spark](building-spark.html): build Spark using the Maven system
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* [Contributing to Spark](https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark)
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* [Supplemental Projects](https://cwiki.apache.org/confluence/display/SPARK/Supplemental+Spark+Projects): related third party Spark projects
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* [Third Party Projects](https://cwiki.apache.org/confluence/display/SPARK/Third+Party+Projects): related third party Spark projects
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**External Resources:**
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@ -110,7 +110,8 @@ head(df)
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SparkR supports operating on a variety of data sources through the `SparkDataFrame` interface. This section describes the general methods for loading and saving data using Data Sources. You can check the Spark SQL programming guide for more [specific options](sql-programming-guide.html#manually-specifying-options) that are available for the built-in data sources.
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The general method for creating SparkDataFrames from data sources is `read.df`. This method takes in the path for the file to load and the type of data source, and the currently active SparkSession will be used automatically. SparkR supports reading JSON, CSV and Parquet files natively and through [Spark Packages](http://spark-packages.org/) you can find data source connectors for popular file formats like [Avro](http://spark-packages.org/package/databricks/spark-avro). These packages can either be added by
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The general method for creating SparkDataFrames from data sources is `read.df`. This method takes in the path for the file to load and the type of data source, and the currently active SparkSession will be used automatically.
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SparkR supports reading JSON, CSV and Parquet files natively, and through packages available from sources like [Third Party Projects](https://cwiki.apache.org/confluence/display/SPARK/Third+Party+Projects), you can find data source connectors for popular file formats like Avro. These packages can either be added by
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specifying `--packages` with `spark-submit` or `sparkR` commands, or if initializing SparkSession with `sparkPackages` parameter when in an interactive R shell or from RStudio.
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<div data-lang="r" markdown="1">
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@ -2382,7 +2382,7 @@ additional effort may be necessary to achieve exactly-once semantics. There are
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- [Kafka Integration Guide](streaming-kafka-integration.html)
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- [Kinesis Integration Guide](streaming-kinesis-integration.html)
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- [Custom Receiver Guide](streaming-custom-receivers.html)
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* Third-party DStream data sources can be found in [Spark Packages](https://spark-packages.org/)
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* Third-party DStream data sources can be found in [Third Party Projects](https://cwiki.apache.org/confluence/display/SPARK/Third+Party+Projects)
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* API documentation
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- Scala docs
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* [StreamingContext](api/scala/index.html#org.apache.spark.streaming.StreamingContext) and
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@ -142,12 +142,13 @@ case class DataSource(
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} else if (provider.toLowerCase == "avro" ||
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provider == "com.databricks.spark.avro") {
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throw new AnalysisException(
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s"Failed to find data source: ${provider.toLowerCase}. Please use Spark " +
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"package http://spark-packages.org/package/databricks/spark-avro")
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s"Failed to find data source: ${provider.toLowerCase}. Please find an Avro " +
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"package at " +
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"https://cwiki.apache.org/confluence/display/SPARK/Third+Party+Projects")
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} else {
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throw new ClassNotFoundException(
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s"Failed to find data source: $provider. Please find packages at " +
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"http://spark-packages.org",
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"https://cwiki.apache.org/confluence/display/SPARK/Third+Party+Projects",
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error)
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}
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}
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@ -1645,21 +1645,18 @@ class SQLQuerySuite extends QueryTest with SharedSQLContext {
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e = intercept[AnalysisException] {
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sql(s"select id from `com.databricks.spark.avro`.`file_path`")
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}
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assert(e.message.contains("Failed to find data source: com.databricks.spark.avro. " +
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"Please use Spark package http://spark-packages.org/package/databricks/spark-avro"))
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assert(e.message.contains("Failed to find data source: com.databricks.spark.avro."))
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// data source type is case insensitive
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e = intercept[AnalysisException] {
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sql(s"select id from Avro.`file_path`")
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}
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assert(e.message.contains("Failed to find data source: avro. Please use Spark package " +
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"http://spark-packages.org/package/databricks/spark-avro"))
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assert(e.message.contains("Failed to find data source: avro."))
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e = intercept[AnalysisException] {
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sql(s"select id from avro.`file_path`")
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}
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assert(e.message.contains("Failed to find data source: avro. Please use Spark package " +
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"http://spark-packages.org/package/databricks/spark-avro"))
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assert(e.message.contains("Failed to find data source: avro."))
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e = intercept[AnalysisException] {
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sql(s"select id from `org.apache.spark.sql.sources.HadoopFsRelationProvider`.`file_path`")
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@ -74,16 +74,16 @@ class ResolvedDataSourceSuite extends SparkFunSuite {
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val error1 = intercept[AnalysisException] {
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getProvidingClass("avro")
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}
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assert(error1.getMessage.contains("spark-packages"))
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assert(error1.getMessage.contains("Failed to find data source: avro."))
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val error2 = intercept[AnalysisException] {
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getProvidingClass("com.databricks.spark.avro")
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}
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assert(error2.getMessage.contains("spark-packages"))
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assert(error2.getMessage.contains("Failed to find data source: com.databricks.spark.avro."))
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val error3 = intercept[ClassNotFoundException] {
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getProvidingClass("asfdwefasdfasdf")
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}
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assert(error3.getMessage.contains("spark-packages"))
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assert(error3.getMessage.contains("Failed to find data source: asfdwefasdfasdf."))
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}
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}
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