diff --git a/python/pyspark/sql.py b/python/pyspark/sql.py index b4e9618cc25b..960d0a82448a 100644 --- a/python/pyspark/sql.py +++ b/python/pyspark/sql.py @@ -117,7 +117,7 @@ def parquetFile(self, path): >>> srdd = sqlCtx.inferSchema(rdd) >>> srdd.saveAsParquetFile(parquetFile) >>> srdd2 = sqlCtx.parquetFile(parquetFile) - >>> srdd.collect() == srdd2.collect() + >>> sorted(srdd.collect()) == sorted(srdd2.collect()) True """ jschema_rdd = self._ssql_ctx.parquetFile(path) @@ -141,7 +141,7 @@ def table(self, tableName): >>> srdd = sqlCtx.inferSchema(rdd) >>> sqlCtx.registerRDDAsTable(srdd, "table1") >>> srdd2 = sqlCtx.table("table1") - >>> srdd.collect() == srdd2.collect() + >>> sorted(srdd.collect()) == sorted(srdd2.collect()) True """ return SchemaRDD(self._ssql_ctx.table(tableName), self) @@ -293,7 +293,7 @@ def saveAsParquetFile(self, path): >>> srdd = sqlCtx.inferSchema(rdd) >>> srdd.saveAsParquetFile(parquetFile) >>> srdd2 = sqlCtx.parquetFile(parquetFile) - >>> srdd2.collect() == srdd.collect() + >>> sorted(srdd2.collect()) == sorted(srdd.collect()) True """ self._jschema_rdd.saveAsParquetFile(path) @@ -307,7 +307,7 @@ def registerAsTable(self, name): >>> srdd = sqlCtx.inferSchema(rdd) >>> srdd.registerAsTable("test") >>> srdd2 = sqlCtx.sql("select * from test") - >>> srdd.collect() == srdd2.collect() + >>> sorted(srdd.collect()) == sorted(srdd2.collect()) True """ self._jschema_rdd.registerAsTable(name) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala index 7ad8edf5a5a6..44b19bca460b 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala @@ -33,6 +33,7 @@ import org.apache.spark.api.java.JavaRDD import java.util.{Map => JMap} /** + * ***FALSE CHANGE*** * :: AlphaComponent :: * An RDD of [[Row]] objects that has an associated schema. In addition to standard RDD functions, * SchemaRDDs can be used in relational queries, as shown in the examples below.