Add support for trace event processing using callacks
Some trace analysis tasks are most easily expressed by iterating over
events in chronological order. Add a run_event_callbacks() method to
the GenericFTrace class that will run user-defined functions on trace
events in the order they occurred.
Signed-off-by: Connor O'Brien <connoro@google.com>
diff --git a/tests/test_ftrace.py b/tests/test_ftrace.py
index 1377c68..2488484 100644
--- a/tests/test_ftrace.py
+++ b/tests/test_ftrace.py
@@ -230,6 +230,31 @@
# Make sure there are no NaNs in the middle of the array
self.assertTrue(allfreqs[0][1]["A57_freq_in"].notnull().all())
+ def test_run_event_callbacks(self):
+ """Test run_event_callbacks()"""
+
+ counts = {
+ "cpu_in_power": 0,
+ "cpu_out_power": 0
+ }
+
+ def cpu_in_power_fn(data):
+ counts["cpu_in_power"] += 1
+
+ def cpu_out_power_fn(data):
+ counts["cpu_out_power"] += 1
+
+ fn_map = {
+ "cpu_in_power": cpu_in_power_fn,
+ "cpu_out_power": cpu_out_power_fn
+ }
+ trace = trappy.FTrace()
+
+ trace.run_event_callbacks(fn_map)
+
+ self.assertEqual(counts["cpu_in_power"], 134)
+ self.assertEqual(counts["cpu_out_power"], 134)
+
def test_plot_freq_hists(self):
"""Test that plot_freq_hists() doesn't bomb"""
diff --git a/trappy/ftrace.py b/trappy/ftrace.py
index 23189d1..cd4d8e2 100644
--- a/trappy/ftrace.py
+++ b/trappy/ftrace.py
@@ -311,6 +311,55 @@
return ret
+ def run_event_callbacks(self, fn_map):
+ """
+ Apply callback functions to trace events in chronological order.
+
+ This method iterates over a user-specified subset of the available trace
+ event dataframes, calling different user-specified functions for each
+ event type. These functions are passed a dictionary mapping 'Index' and
+ the column names to their values for that row.
+
+ For example, to iterate over trace t, applying your functions callback_fn1
+ and callback_fn2 to each sched_switch and sched_wakeup event respectively:
+
+ t.run_event_callbacks({
+ "sched_switch": callback_fn1,
+ "sched_wakeup": callback_fn2
+ })
+ """
+ dfs = {event: getattr(self, event).data_frame for event in fn_map.keys()}
+ events = [event for event in fn_map.keys() if not dfs[event].empty]
+ iters = {event: dfs[event].itertuples() for event in events}
+ next_rows = {event: iterator.next() for event,iterator in iters.iteritems()}
+
+ # Column names beginning with underscore will not be preserved in tuples
+ # due to constraints on namedtuple field names, so store mappings from
+ # column name to column number for each trace event.
+ col_idxs = {event: {
+ name: idx for idx, name in enumerate(
+ ['Index'] + dfs[event].columns.tolist()
+ )
+ } for event in events}
+
+ def getLine(event):
+ line_col_idx = col_idxs[event]['__line']
+ return next_rows[event][line_col_idx]
+
+ while events:
+ event_name = min(events, key=getLine)
+ event_tuple = next_rows[event_name]
+
+ event_dict = {
+ col: event_tuple[idx] for col, idx in col_idxs[event_name].iteritems()
+ }
+ fn_map[event_name](event_dict)
+ event_row = next(iters[event_name], None)
+ if event_row:
+ next_rows[event_name] = event_row
+ else:
+ events.remove(event_name)
+
def plot_freq_hists(self, map_label, ax):
"""Plot histograms for each actor input and output frequency