Support for 'interval' filter (#87)

Author: var23rav

pydruid/utils/filters.py

@@ -61,6 +61,10 @@ def __init__(self, **args):
         elif args["type"] == "columnComparison":
             self.filter = {"filter": {"type": "columnComparison",
                                       "dimensions": args["dimensions"]}}
+        elif args["type"] == "interval":
+            self.filter = {"filter": {"type": "interval",
+                                      "dimension": args["dimension"],
+                                      "intervals": args["intervals"]}}
         else:
             raise NotImplementedError(
                 'Filter type: {0} does not exist'.format(args['type']))
@@ -140,3 +144,18 @@ def __init__(self, dimension, lower, upper, lowerStrict=False, upperStrict=False
             lower=lower, upper=upper,
             lowerStrict=lowerStrict, upperStrict=upperStrict,
             alphaNumeric=alphaNumeric)
+
+
+class Interval(Filter):
+    """
+    Interval filter can be used to filter by comparing dimension(__time) values to a list of intervals.
+
+    :ivar str dimension: Dimension to filter on.
+    :ivar list intervals: List of ISO-8601 intervals of data to filter out.
+    """
+    def __init__(self, dimension, intervals):
+
+        Filter.__init__(self,
+            type='interval', dimension=dimension,
+            intervals=intervals)
+

tests/utils/test_filters.py

@@ -42,6 +42,12 @@ def test_bound_filter(self):
         expected = {'type': 'bound', 'dimension': 'dim', 'lower': '1', 'lowerStrict': True, 'upper': '10', 'upperStrict': True, 'alphaNumeric': True}
         assert actual == expected
 
+    def test_interval_filter(self):
+        actual = filters.Filter.build_filter(
+            filters.Interval(dimension='dim', intervals=["2014-10-01T00:00:00.000Z/2014-10-07T00:00:00.000Z"]))
+        expected = {'type': 'interval', 'dimension': 'dim', 'intervals': ["2014-10-01T00:00:00.000Z/2014-10-07T00:00:00.000Z"]}
+        assert actual == expected
+
     def test_and_filter(self):
         f1 = filters.Filter(dimension='dim1', value='val1')
         f2 = filters.Filter(dimension='dim2', value='val2')