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author | Sean R. Owen <srowen@apache.org> | 2015-03-16 13:49:54 +0000 |
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committer | Sean R. Owen <srowen@apache.org> | 2015-03-16 13:49:54 +0000 |
commit | 9695c4519404b689f29bc0fbc1a2eefa3eb33806 (patch) | |
tree | 15bf6c9092256ac57fd98dd52af2ee40206ad6b3 /site | |
parent | 509e19f3327999a99c5c41a956e3966beeebcaba (diff) | |
download | spark-website-9695c4519404b689f29bc0fbc1a2eefa3eb33806.tar.gz spark-website-9695c4519404b689f29bc0fbc1a2eefa3eb33806.tar.bz2 spark-website-9695c4519404b689f29bc0fbc1a2eefa3eb33806.zip |
Removed extra word 'extended'
Diffstat (limited to 'site')
-rw-r--r-- | site/releases/spark-release-1-3-0.html | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/site/releases/spark-release-1-3-0.html b/site/releases/spark-release-1-3-0.html index 4fa5fba8e..e15dcda59 100644 --- a/site/releases/spark-release-1-3-0.html +++ b/site/releases/spark-release-1-3-0.html @@ -195,7 +195,7 @@ <h2 id="upgrading-to-spark-13">Upgrading to Spark 1.3</h2> <p>Spark 1.3 is binary compatible with Spark 1.X releases, so no code changes are necessary. This excludes API’s marked explicitly as unstable.</p> -<p>As part of stabilizing the Spark SQL API, the <code>SchemaRDD</code> class has been extended renamed to <code>DataFrame</code>. Spark SQL’s <a href="http://spark.apache.org/docs/1.3.0/sql-programming-guide.html#migration-guide">migration guide</a> describes the upgrade process in detail. Spark SQL also now requires that column identifiers which use reserved words (such as “string” or “table”) be escaped using backticks.</p> +<p>As part of stabilizing the Spark SQL API, the <code>SchemaRDD</code> class has been renamed to <code>DataFrame</code>. Spark SQL’s <a href="http://spark.apache.org/docs/1.3.0/sql-programming-guide.html#migration-guide">migration guide</a> describes the upgrade process in detail. Spark SQL also now requires that column identifiers which use reserved words (such as “string” or “table”) be escaped using backticks.</p> <h3 id="known-issues">Known Issues</h3> <p>This release has few known issues which will be addressed in Spark 1.3.1:</p> |