Github user feynmanliang commented on a diff in the pull request: https://github.com/apache/spark/pull/7854#discussion_r37826150 --- Diff: python/pyspark/mllib/linalg/__init__.py --- @@ -461,32 +461,41 @@ def __init__(self, size, *args): self.size = int(size) """ Size of the vector. """ assert 1 <= len(args) <= 2, "must pass either 2 or 3 arguments" - if len(args) == 1: - pairs = args[0] - if type(pairs) == dict: - pairs = pairs.items() - pairs = sorted(pairs) - self.indices = np.array([p[0] for p in pairs], dtype=np.int32) - """ A list of indices corresponding to active entries. """ - self.values = np.array([p[1] for p in pairs], dtype=np.float64) - """ A list of values corresponding to active entries. """ + if isinstance(args[0], bytes): + assert isinstance(args[1], bytes), "values should be string too" + if args[0]: + self.indices = np.frombuffer(args[0], np.int32) + self.values = np.frombuffer(args[1], np.float64) + else: + # np.frombuffer() doesn't work well with empty string in older version + self.indices = np.array([], dtype=np.int32) + self.values = np.array([], dtype=np.float64) else: - if isinstance(args[0], bytes): - assert isinstance(args[1], bytes), "values should be string too" - if args[0]: - self.indices = np.frombuffer(args[0], np.int32) - self.values = np.frombuffer(args[1], np.float64) - else: - # np.frombuffer() doesn't work well with empty string in older version - self.indices = np.array([], dtype=np.int32) - self.values = np.array([], dtype=np.float64) + if len(args) == 1: + args = args[0] + if isinstance(args, dict): + args = args.items() + args = list(zip(*args)) + + # Handle empty args case. + if len(args) == 0: + indices = [] + values = [] else: - self.indices = np.array(args[0], dtype=np.int32) - self.values = np.array(args[1], dtype=np.float64) - assert len(self.indices) == len(self.values), "index and value arrays not same length" - for i in xrange(len(self.indices) - 1): - if self.indices[i] >= self.indices[i + 1]: - raise TypeError("indices array must be sorted") --- End diff -- Yeah, but the PR I linked (and maybe other parts of the code) depend on sorted indices. Have we checked if the ordering of indices is assumed elsewhere in the code? Also, Python's `sorted` uses timsort internally which has O(n) complexity for an already sorted input so the overhead is not terrible.
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