Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/5173#discussion_r27268071
--- Diff: python/pyspark/context.py ---
@@ -456,7 +463,7 @@ def _dictToJavaMap(self, d):
jm = self._jvm.java.util.HashMap()
if not d:
d = {}
- for k, v in d.iteritems():
+ for k, v in d.items():
--- End diff --
The overhead of items() for dict with 1 million items is just 80 ms, so I'd
like go with it.
```
davies@localhost:~/work/spark$ python -m timeit -s
"d=dict(zip(range(1<<20), range(1<<20)))" -c "sum(1 for _ in d.iteritems())"
10 loops, best of 3: 80.7 msec per loop
davies@localhost:~/work/spark$ python -m timeit -s
"d=dict(zip(range(1<<20), range(1<<20)))" -c "sum(1 for _ in d.items())"
10 loops, best of 3: 162 msec per loop
```
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