def fetch_points(self,
metric,
time_start,
time_end,
stage,
aggregated=True):
"""See the real Accessor for a description."""
super(_MemoryAccessor, self).fetch_points(metric, time_start, time_end,
stage)
points = self._metric_to_points[(metric.name, stage)]
rows = []
for ts in points.irange(time_start, time_end):
# A row is time_base_ms, time_offset_ms, value, count
if stage.aggregated():
row = self.Row(ts * 1000.0, 0, 0, float(points[ts][0]),
points[ts][1])
else:
row = self.Row0(ts * 1000.0, 0, float(points[ts][0]))
rows.append(row)
query_results = [(True, rows)]
time_start_ms = int(time_start) * 1000
time_end_ms = int(time_end) * 1000
return bg_accessor.PointGrouper(
metric,
time_start_ms,
time_end_ms,
stage,
query_results,
aggregated=aggregated,
)
def test_basic(self):
"""Test that we can read simple stages."""
stage = _METRIC.metadata.retention.stage0
data = [(True, [(0, 0, 1), (0, 1, 2)]), (True, [(0, 2, 3)])]
results = bg_accessor.PointGrouper(_METRIC, 0, 3600, stage, data)
expected_results = [(0.0, 1), (1.0, 2), (2.0, 3)]
self.assertEquals(list(results), expected_results)
def test_without_aggregating(self):
"""Test that we can merge instead of aggregate a stage."""
stage0 = _METRIC.metadata.retention.stage0
stage1 = _METRIC.metadata.retention.stages[1]
data = [(True, [(0, 0, 1), (0, 1, 2)]), (True, [(0, 2, 3)])]
results = bg_accessor.PointGrouper(
_METRIC, 0, 3600, stage1, data, source_stage=stage0, aggregated=False)
expected_results = [(0.0, 6.0, 3.0)]
self.assertEquals(list(results), expected_results)
def test_downsampling(self):
"""Test that we can downsample a stage."""
stage0 = _METRIC.metadata.retention.stage0
stage1 = _METRIC.metadata.retention.stages[1]
data = [(True, [(0, 0, 1), (0, 1, 2)]), (True, [(0, 2, 3)])]
results = bg_accessor.PointGrouper(
_METRIC, 0, 3600, stage1, data, source_stage=stage0)
expected_results = [(0.0, 2.0)]
self.assertEquals(list(results), expected_results)
def test_aggregated(self):
"""Test that we can read aggregated stages."""
stage1 = _METRIC.metadata.retention.stages[1]
replica0, replica1 = 0xFFFF, 0x0000
data = [
(True, [(0, 0, replica0, 1, 1), (0, 1, replica0, 2, 2)]),
(True, [(0, 1, replica1, 2, 4)])
]
results = bg_accessor.PointGrouper(_METRIC, 0, 86000, stage1, data)
expected_results = [(0.0, 1.0), (60.0, 0.5)]
self.assertEquals(list(results), expected_results)
