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authorTathagata Das <tathagata.das1565@gmail.com>2015-09-04 23:16:39 -1000
committerReynold Xin <rxin@databricks.com>2015-09-04 23:16:39 -1000
commit7a4f326c00fb33c384b4fb927310d687ec063329 (patch)
treef10a667018ac01e4aa4bc384d8ec72cd64aac27a /docs
parent6c751940ea8449b7540ba956a00ed19ba0af599b (diff)
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[SPARK-10440] [STREAMING] [DOCS] Update python API stuff in the programming guides and python docs
- Fixed information around Python API tags in streaming programming guides - Added missing stuff in python docs Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #8595 from tdas/SPARK-10440.
Diffstat (limited to 'docs')
-rw-r--r--docs/streaming-flume-integration.md2
-rw-r--r--docs/streaming-programming-guide.md14
2 files changed, 4 insertions, 12 deletions
diff --git a/docs/streaming-flume-integration.md b/docs/streaming-flume-integration.md
index de0461010d..383d954409 100644
--- a/docs/streaming-flume-integration.md
+++ b/docs/streaming-flume-integration.md
@@ -5,8 +5,6 @@ title: Spark Streaming + Flume Integration Guide
[Apache Flume](https://flume.apache.org/) is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. Here we explain how to configure Flume and Spark Streaming to receive data from Flume. There are two approaches to this.
-<span class="badge" style="background-color: grey">Python API</span> Flume is not yet available in the Python API.
-
## Approach 1: Flume-style Push-based Approach
Flume is designed to push data between Flume agents. In this approach, Spark Streaming essentially sets up a receiver that acts an Avro agent for Flume, to which Flume can push the data. Here are the configuration steps.
diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md
index 118ced298f..a1acf83f75 100644
--- a/docs/streaming-programming-guide.md
+++ b/docs/streaming-programming-guide.md
@@ -50,13 +50,7 @@ all of which are presented in this guide.
You will find tabs throughout this guide that let you choose between code snippets of
different languages.
-**Note:** Python API for Spark Streaming has been introduced in Spark 1.2. It has all the DStream
-transformations and almost all the output operations available in Scala and Java interfaces.
-However, it only has support for basic sources like text files and text data over sockets.
-APIs for additional sources, like Kafka and Flume, will be available in the future.
-Further information about available features in the Python API are mentioned throughout this
-document; look out for the tag
-<span class="badge" style="background-color: grey">Python API</span>.
+**Note:** There are a few APIs that are either different or not available in Python. Throughout this guide, you will find the tag <span class="badge" style="background-color: grey">Python API</span> highlighting these differences.
***************************************************************************************************
@@ -683,7 +677,7 @@ for Java, and [StreamingContext](api/python/pyspark.streaming.html#pyspark.strea
{:.no_toc}
<span class="badge" style="background-color: grey">Python API</span> As of Spark {{site.SPARK_VERSION_SHORT}},
-out of these sources, *only* Kafka, Flume and MQTT are available in the Python API. We will add more advanced sources in the Python API in future.
+out of these sources, Kafka, Kinesis, Flume and MQTT are available in the Python API.
This category of sources require interfacing with external non-Spark libraries, some of them with
complex dependencies (e.g., Kafka and Flume). Hence, to minimize issues related to version conflicts
@@ -725,9 +719,9 @@ Some of these advanced sources are as follows.
- **Kafka:** Spark Streaming {{site.SPARK_VERSION_SHORT}} is compatible with Kafka 0.8.2.1. See the [Kafka Integration Guide](streaming-kafka-integration.html) for more details.
-- **Flume:** Spark Streaming {{site.SPARK_VERSION_SHORT}} is compatible with Flume 1.4.0. See the [Flume Integration Guide](streaming-flume-integration.html) for more details.
+- **Flume:** Spark Streaming {{site.SPARK_VERSION_SHORT}} is compatible with Flume 1.6.0. See the [Flume Integration Guide](streaming-flume-integration.html) for more details.
-- **Kinesis:** See the [Kinesis Integration Guide](streaming-kinesis-integration.html) for more details.
+- **Kinesis:** Spark Streaming {{site.SPARK_VERSION_SHORT}} is compatible with Kinesis Client Library 1.2.1. See the [Kinesis Integration Guide](streaming-kinesis-integration.html) for more details.
- **Twitter:** Spark Streaming's TwitterUtils uses Twitter4j 3.0.3 to get the public stream of tweets using
[Twitter's Streaming API](https://dev.twitter.com/docs/streaming-apis). Authentication information