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-rw-r--r--examples/src/main/python/sql/hive.py2
1 files changed, 1 insertions, 1 deletions
diff --git a/examples/src/main/python/sql/hive.py b/examples/src/main/python/sql/hive.py
index 1f175d7258..1f83a6fb48 100644
--- a/examples/src/main/python/sql/hive.py
+++ b/examples/src/main/python/sql/hive.py
@@ -68,7 +68,7 @@ if __name__ == "__main__":
# The results of SQL queries are themselves DataFrames and support all normal functions.
sqlDF = spark.sql("SELECT key, value FROM src WHERE key < 10 ORDER BY key")
- # The items in DaraFrames are of type Row, which allows you to access each column by ordinal.
+ # The items in DataFrames are of type Row, which allows you to access each column by ordinal.
stringsDS = sqlDF.rdd.map(lambda row: "Key: %d, Value: %s" % (row.key, row.value))
for record in stringsDS.collect():
print(record)