You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@spark.apache.org by gu...@apache.org on 2019/05/10 08:55:56 UTC
[spark] branch master updated: [MINOR][DOCS] Make Spark's
description consistent in docs with websites
This is an automated email from the ASF dual-hosted git repository.
gurwls223 pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/spark.git
The following commit(s) were added to refs/heads/master by this push:
new cfe236f [MINOR][DOCS] Make Spark's description consistent in docs with websites
cfe236f is described below
commit cfe236f6957dd9ae799831d47914de34a03716aa
Author: Reynold Xin <rx...@databricks.com>
AuthorDate: Fri May 10 17:55:23 2019 +0900
[MINOR][DOCS] Make Spark's description consistent in docs with websites
We updated our website a long time ago to describe Spark as the unified analytics engine, which is also how Spark is described in the community now. But our README and docs page still use the same description from 2011 ... This patch updates them.
The patch also updates the README example to use more modern APIs, and refer to Structured Streaming rather than Spark Streaming.
Closes #24573 from rxin/consistent-message.
Authored-by: Reynold Xin <rx...@databricks.com>
Signed-off-by: HyukjinKwon <gu...@apache.org>
---
README.md | 20 ++++++++++----------
docs/index.md | 4 ++--
python/README.md | 4 ++--
3 files changed, 14 insertions(+), 14 deletions(-)
diff --git a/README.md b/README.md
index 271f2f5..482c007 100644
--- a/README.md
+++ b/README.md
@@ -1,18 +1,18 @@
# Apache Spark
-[](https://amplab.cs.berkeley.edu/jenkins/job/spark-master-test-sbt-hadoop-2.7)
-[](https://ci.appveyor.com/project/ApacheSoftwareFoundation/spark)
-[](https://spark-test.github.io/pyspark-coverage-site)
-
-Spark is a fast and general cluster computing system for Big Data. It provides
+Spark is a unified analytics engine for large-scale data processing. It provides
high-level APIs in Scala, Java, Python, and R, and an optimized engine that
supports general computation graphs for data analysis. It also supports a
rich set of higher-level tools including Spark SQL for SQL and DataFrames,
MLlib for machine learning, GraphX for graph processing,
-and Spark Streaming for stream processing.
+and Structured Streaming for stream processing.
<http://spark.apache.org/>
+[](https://amplab.cs.berkeley.edu/jenkins/job/spark-master-test-sbt-hadoop-2.7)
+[](https://ci.appveyor.com/project/ApacheSoftwareFoundation/spark)
+[](https://spark-test.github.io/pyspark-coverage-site)
+
## Online Documentation
@@ -41,9 +41,9 @@ The easiest way to start using Spark is through the Scala shell:
./bin/spark-shell
-Try the following command, which should return 1000:
+Try the following command, which should return 1,000,000,000:
- scala> sc.parallelize(1 to 1000).count()
+ scala> spark.range(1000 * 1000 * 1000).count()
## Interactive Python Shell
@@ -51,9 +51,9 @@ Alternatively, if you prefer Python, you can use the Python shell:
./bin/pyspark
-And run the following command, which should also return 1000:
+And run the following command, which should also return 1,000,000,000:
- >>> sc.parallelize(range(1000)).count()
+ >>> spark.range(1000 * 1000 * 1000).count()
## Example Programs
diff --git a/docs/index.md b/docs/index.md
index 5adbebd..bec0fee 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -20,10 +20,10 @@ license: |
limitations under the License.
---
-Apache Spark is a fast and general-purpose cluster computing system.
+Apache Spark is a unified analytics engine for large-scale data processing.
It provides high-level APIs in Java, Scala, Python and R,
and an optimized engine that supports general execution graphs.
-It also supports a rich set of higher-level tools including [Spark SQL](sql-programming-guide.html) for SQL and structured data processing, [MLlib](ml-guide.html) for machine learning, [GraphX](graphx-programming-guide.html) for graph processing, and [Spark Streaming](streaming-programming-guide.html).
+It also supports a rich set of higher-level tools including [Spark SQL](sql-programming-guide.html) for SQL and structured data processing, [MLlib](ml-guide.html) for machine learning, [GraphX](graphx-programming-guide.html) for graph processing, and [Structured Streaming](structured-streaming-programming-guide.html) for incremental computation and stream processing.
# Security
diff --git a/python/README.md b/python/README.md
index ffb6147..d775b65 100644
--- a/python/README.md
+++ b/python/README.md
@@ -1,11 +1,11 @@
# Apache Spark
-Spark is a fast and general cluster computing system for Big Data. It provides
+Spark is a unified analytics engine for large-scale data processing. It provides
high-level APIs in Scala, Java, Python, and R, and an optimized engine that
supports general computation graphs for data analysis. It also supports a
rich set of higher-level tools including Spark SQL for SQL and DataFrames,
MLlib for machine learning, GraphX for graph processing,
-and Spark Streaming for stream processing.
+and Structured Streaming for stream processing.
<http://spark.apache.org/>
---------------------------------------------------------------------
To unsubscribe, e-mail: commits-unsubscribe@spark.apache.org
For additional commands, e-mail: commits-help@spark.apache.org