Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2313#discussion_r17222379
--- Diff: python/pyspark/rddsampler.py ---
@@ -22,24 +22,26 @@
class RDDSamplerBase(object):
def __init__(self, withReplacement, seed=None):
- try:
- import numpy
- self._use_numpy = True
- except ImportError:
- print >> sys.stderr, (
- "NumPy does not appear to be installed. "
- "Falling back to default random generator for sampling.")
- self._use_numpy = False
-
self._seed = seed if seed is not None else random.randint(0,
sys.maxint)
self._withReplacement = withReplacement
self._random = None
self._split = None
self._rand_initialized = False
+ self._tried_numpy = False
def initRandomGenerator(self, split):
+ if not self._tried_numpy:
+ try:
+ import numpy
+ self._use_numpy = True
+ except ImportError:
+ print >> sys.stderr, (
+ "NumPy does not appear to be installed. "
+ "Falling back to default random generator for
sampling.")
+ self._use_numpy = False
+ self._tried_numpy = True
+
--- End diff --
How about put detecting numpy and fallback at the module level?
Such as:
```python
try:
from numpy.random import RandomState
except ImportError:
class RandomState(object):
def __init__(self, seed):
self._random = random.Random(seed)
def random_sample(self):
pass
def poisson(self):
pass
def shuffle(self):
pass
```
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