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Posted to commits@spark.apache.org by sr...@apache.org on 2015/06/05 14:24:02 UTC
spark git commit: [STREAMING] Update streaming-kafka-integration.md
Repository: spark
Updated Branches:
refs/heads/master b16b5434f -> 019dc9f55
[STREAMING] Update streaming-kafka-integration.md
Fixed the broken links (Examples) in the documentation.
Author: Akhil Das <ak...@darktech.ca>
Closes #6666 from akhld/patch-2 and squashes the following commits:
2228b83 [Akhil Das] Update streaming-kafka-integration.md
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/019dc9f5
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/019dc9f5
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/019dc9f5
Branch: refs/heads/master
Commit: 019dc9f558cf7c0b708d3b1f0882b0c19134ffb6
Parents: b16b543
Author: Akhil Das <ak...@darktech.ca>
Authored: Fri Jun 5 14:23:23 2015 +0200
Committer: Sean Owen <so...@cloudera.com>
Committed: Fri Jun 5 14:23:23 2015 +0200
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docs/streaming-kafka-integration.md | 10 +++++-----
1 file changed, 5 insertions(+), 5 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/019dc9f5/docs/streaming-kafka-integration.md
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diff --git a/docs/streaming-kafka-integration.md b/docs/streaming-kafka-integration.md
index 64714f0..d6d5605 100644
--- a/docs/streaming-kafka-integration.md
+++ b/docs/streaming-kafka-integration.md
@@ -29,7 +29,7 @@ Next, we discuss how to use this approach in your streaming application.
[ZK quorum], [consumer group id], [per-topic number of Kafka partitions to consume])
You can also specify the key and value classes and their corresponding decoder classes using variations of `createStream`. See the [API docs](api/scala/index.html#org.apache.spark.streaming.kafka.KafkaUtils$)
- and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala).
+ and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala).
</div>
<div data-lang="java" markdown="1">
import org.apache.spark.streaming.kafka.*;
@@ -39,7 +39,7 @@ Next, we discuss how to use this approach in your streaming application.
[ZK quorum], [consumer group id], [per-topic number of Kafka partitions to consume]);
You can also specify the key and value classes and their corresponding decoder classes using variations of `createStream`. See the [API docs](api/java/index.html?org/apache/spark/streaming/kafka/KafkaUtils.html)
- and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/scala-2.10/src/main/java/org/apache/spark/examples/streaming/JavaKafkaWordCount.java).
+ and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/src/main/java/org/apache/spark/examples/streaming/JavaKafkaWordCount.java).
</div>
<div data-lang="python" markdown="1">
@@ -105,7 +105,7 @@ Next, we discuss how to use this approach in your streaming application.
streamingContext, [map of Kafka parameters], [set of topics to consume])
See the [API docs](api/scala/index.html#org.apache.spark.streaming.kafka.KafkaUtils$)
- and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/DirectKafkaWordCount.scala).
+ and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/src/main/scala/org/apache/spark/examples/streaming/DirectKafkaWordCount.scala).
</div>
<div data-lang="java" markdown="1">
import org.apache.spark.streaming.kafka.*;
@@ -116,7 +116,7 @@ Next, we discuss how to use this approach in your streaming application.
[map of Kafka parameters], [set of topics to consume]);
See the [API docs](api/java/index.html?org/apache/spark/streaming/kafka/KafkaUtils.html)
- and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/scala-2.10/src/main/java/org/apache/spark/examples/streaming/JavaDirectKafkaWordCount.java).
+ and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/src/main/java/org/apache/spark/examples/streaming/JavaDirectKafkaWordCount.java).
</div>
</div>
@@ -153,4 +153,4 @@ Next, we discuss how to use this approach in your streaming application.
Another thing to note is that since this approach does not use Receivers, the standard receiver-related (that is, [configurations](configuration.html) of the form `spark.streaming.receiver.*` ) will not apply to the input DStreams created by this approach (will apply to other input DStreams though). Instead, use the [configurations](configuration.html) `spark.streaming.kafka.*`. An important one is `spark.streaming.kafka.maxRatePerPartition` which is the maximum rate at which each Kafka partition will be read by this direct API.
-3. **Deploying:** Similar to the first approach, you can package `spark-streaming-kafka_{{site.SCALA_BINARY_VERSION}}` and its dependencies into the application JAR and the launch the application using `spark-submit`. Make sure `spark-core_{{site.SCALA_BINARY_VERSION}}` and `spark-streaming_{{site.SCALA_BINARY_VERSION}}` are marked as `provided` dependencies as those are already present in a Spark installation.
\ No newline at end of file
+3. **Deploying:** Similar to the first approach, you can package `spark-streaming-kafka_{{site.SCALA_BINARY_VERSION}}` and its dependencies into the application JAR and the launch the application using `spark-submit`. Make sure `spark-core_{{site.SCALA_BINARY_VERSION}}` and `spark-streaming_{{site.SCALA_BINARY_VERSION}}` are marked as `provided` dependencies as those are already present in a Spark installation.
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