Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/12860#discussion_r61928851
--- Diff: examples/src/main/python/sql.py ---
@@ -57,24 +52,22 @@
else:
path = sys.argv[1]
# Create a DataFrame from the file(s) pointed to by path
- people = sqlContext.jsonFile(path)
+ people = spark.read.json(path)
# root
# |-- person_name: string (nullable = false)
# |-- person_age: integer (nullable = false)
# The inferred schema can be visualized using the printSchema() method.
people.printSchema()
# root
- # |-- age: IntegerType
- # |-- name: StringType
+ # |-- age: long (nullable = true)
+ # |-- name: string (nullable = true)
# Register this DataFrame as a table.
- people.registerAsTable("people")
+ people.registerTempTable("people")
# SQL statements can be run by using the sql methods provided by
sqlContext
- teenagers = sqlContext.sql("SELECT name FROM people WHERE age >= 13
AND age <= 19")
+ teenagers = spark.sql("SELECT name FROM people WHERE age >= 13 AND age
<= 19")
for each in teenagers.collect():
print(each[0])
-
- sc.stop()
--- End diff --
we still need to do this. Once we merge #12873 we'll have a `spark.stop()`
method available in scala.
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