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author | Sean Zhong <seanzhong@databricks.com> | 2016-05-18 09:01:59 +0800 |
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committer | Cheng Lian <lian@databricks.com> | 2016-05-18 09:01:59 +0800 |
commit | 25b315e6cad7c27b62dcaa2c194293c1115fdfb3 (patch) | |
tree | cfeebcaf553d78ca80a70f7139a765e7759f0410 /python/pyspark/sql/context.py | |
parent | b674e67c22bf663334e537e35787c00533adbb04 (diff) | |
download | spark-25b315e6cad7c27b62dcaa2c194293c1115fdfb3.tar.gz spark-25b315e6cad7c27b62dcaa2c194293c1115fdfb3.tar.bz2 spark-25b315e6cad7c27b62dcaa2c194293c1115fdfb3.zip |
[SPARK-15171][SQL] Remove the references to deprecated method dataset.registerTempTable
## What changes were proposed in this pull request?
Update the unit test code, examples, and documents to remove calls to deprecated method `dataset.registerTempTable`.
## How was this patch tested?
This PR only changes the unit test code, examples, and comments. It should be safe.
This is a follow up of PR https://github.com/apache/spark/pull/12945 which was merged.
Author: Sean Zhong <seanzhong@databricks.com>
Closes #13098 from clockfly/spark-15171-remove-deprecation.
Diffstat (limited to 'python/pyspark/sql/context.py')
-rw-r--r-- | python/pyspark/sql/context.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/python/pyspark/sql/context.py b/python/pyspark/sql/context.py index ca111ae9bb..e8e60c6412 100644 --- a/python/pyspark/sql/context.py +++ b/python/pyspark/sql/context.py @@ -57,7 +57,7 @@ class SQLContext(object): ... b=True, list=[1, 2, 3], dict={"s": 0}, row=Row(a=1), ... time=datetime(2014, 8, 1, 14, 1, 5))]) >>> df = allTypes.toDF() - >>> df.registerTempTable("allTypes") + >>> df.createOrReplaceTempView("allTypes") >>> sqlContext.sql('select i+1, d+1, not b, list[1], dict["s"], time, row.a ' ... 'from allTypes where b and i > 0').collect() [Row((i + CAST(1 AS BIGINT))=2, (d + CAST(1 AS DOUBLE))=2.0, (NOT b)=False, list[1]=2, \ @@ -106,7 +106,7 @@ class SQLContext(object): def newSession(self): """ Returns a new SQLContext as new session, that has separate SQLConf, - registered temporary tables and UDFs, but shared SparkContext and + registered temporary views and UDFs, but shared SparkContext and table cache. """ return self.__class__(self._sc, self.sparkSession.newSession()) |