From f92f334ca47c03b980b06cf300aa652d0ffa1880 Mon Sep 17 00:00:00 2001
From: Jason White <jason.white@shopify.com>
Date: Mon, 2 Nov 2015 10:49:06 -0800
Subject: [PATCH] [SPARK-11437] [PYSPARK] Don't .take when converting RDD to
DataFrame with provided schema
When creating a DataFrame from an RDD in PySpark, `createDataFrame` calls `.take(10)` to verify the first 10 rows of the RDD match the provided schema. Similar to https://issues.apache.org/jira/browse/SPARK-8070, but that issue affected cases where a schema was not provided.
Verifying the first 10 rows is of limited utility and causes the DAG to be executed non-lazily. If necessary, I believe this verification should be done lazily on all rows. However, since the caller is providing a schema to follow, I think it's acceptable to simply fail if the schema is incorrect.
marmbrus We chatted about this at SparkSummitEU. davies you made a similar change for the infer-schema path in https://github.com/apache/spark/pull/6606
Author: Jason White <jason.white@shopify.com>
Closes #9392 from JasonMWhite/createDataFrame_without_take.
---
python/pyspark/sql/context.py | 8 +-------
1 file changed, 1 insertion(+), 7 deletions(-)
diff --git a/python/pyspark/sql/context.py b/python/pyspark/sql/context.py
index 79453658a1..924bb6433d 100644
--- a/python/pyspark/sql/context.py
+++ b/python/pyspark/sql/context.py
@@ -318,13 +318,7 @@ class SQLContext(object):
struct.names[i] = name
schema = struct
- elif isinstance(schema, StructType):
- # take the first few rows to verify schema
- rows = rdd.take(10)
- for row in rows:
- _verify_type(row, schema)
-
- else:
+ elif not isinstance(schema, StructType):
raise TypeError("schema should be StructType or list or None, but got: %s" % schema)
# convert python objects to sql data
--
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