histogram: support sorting bucket before dumping table

When there are multiple fields in the secondary key of a histogram
(e.g. output the bio latency for each combination of disk and blk cgroup),
if the buckets are not sorted before the iteration, the output order
of tables often does not meet our expectations.

So provide a way to sort them.

src/python/bcc/table.py

@@ -275,9 +275,11 @@ class TableBase(MutableMapping):
         return next_key
 
     def print_log2_hist(self, val_type="value", section_header="Bucket ptr",
-            section_print_fn=None, bucket_fn=None, strip_leading_zero=None):
+            section_print_fn=None, bucket_fn=None, strip_leading_zero=None,
+            bucket_sort_fn=None):
         """print_log2_hist(val_type="value", section_header="Bucket ptr",
-                           section_print_fn=None, bucket_fn=None)
+                           section_print_fn=None, bucket_fn=None,
+                           strip_leading_zero=None, bucket_sort_fn=None):
 
         Prints a table as a log2 histogram. The table must be stored as
         log2. The val_type argument is optional, and is a column header.
@@ -287,9 +289,12 @@ class TableBase(MutableMapping):
         to format into a string as it sees fit. If bucket_fn is not None,
         it will be used to produce a bucket value for the histogram keys.
         If the value of strip_leading_zero is not False, prints a histogram
-        that is omitted leading zeros from the beginning. The maximum index
-        allowed is log2_index_max (65), which will accommodate any 64-bit
-        integer in the histogram.
+        that is omitted leading zeros from the beginning.
+        If bucket_sort_fn is not None, it will be used to sort the buckets
+        before iterating them, and it is useful when there are multiple fields
+        in the secondary key.
+        The maximum index allowed is log2_index_max (65), which will
+        accommodate any 64-bit integer in the histogram.
         """
         if isinstance(self.Key(), ct.Structure):
             tmp = {}
@@ -302,7 +307,13 @@ class TableBase(MutableMapping):
                 vals = tmp[bucket] = tmp.get(bucket, [0] * log2_index_max)
                 slot = getattr(k, f2)
                 vals[slot] = v.value
-            for bucket, vals in tmp.items():
+
+            buckets = tmp.keys()
+            if bucket_sort_fn:
+                buckets = bucket_sort_fn(buckets)
+
+            for bucket in buckets:
+                vals = tmp[bucket]
                 if section_print_fn:
                     print("\n%s = %s" % (section_header,
                         section_print_fn(bucket)))
@@ -316,9 +327,10 @@ class TableBase(MutableMapping):
             _print_log2_hist(vals, val_type, strip_leading_zero)
 
     def print_linear_hist(self, val_type="value", section_header="Bucket ptr",
-            section_print_fn=None, bucket_fn=None):
+            section_print_fn=None, bucket_fn=None, bucket_sort_fn=None):
         """print_linear_hist(val_type="value", section_header="Bucket ptr",
-                           section_print_fn=None, bucket_fn=None)
+                           section_print_fn=None, bucket_fn=None,
+                           bucket_sort_fn=None)
 
         Prints a table as a linear histogram. This is intended to span integer
         ranges, eg, from 0 to 100. The val_type argument is optional, and is a
@@ -327,6 +339,9 @@ class TableBase(MutableMapping):
         each.  If section_print_fn is not None, it will be passed the bucket
         value to format into a string as it sees fit. If bucket_fn is not None,
         it will be used to produce a bucket value for the histogram keys.
+        If bucket_sort_fn is not None, it will be used to sort the buckets
+        before iterating them, and it is useful when there are multiple fields
+        in the secondary key.
         The maximum index allowed is linear_index_max (1025), which is hoped
         to be sufficient for integer ranges spanned.
         """
@@ -341,7 +356,13 @@ class TableBase(MutableMapping):
                 vals = tmp[bucket] = tmp.get(bucket, [0] * linear_index_max)
                 slot = getattr(k, f2)
                 vals[slot] = v.value
-            for bucket, vals in tmp.items():
+
+            buckets = tmp.keys()
+            if bucket_sort_fn:
+                buckets = bucket_sort_fn(buckets)
+
+            for bucket in buckets:
+                vals = tmp[bucket]
                 if section_print_fn:
                     print("\n%s = %s" % (section_header,
                         section_print_fn(bucket)))