On Sun, Apr 14, 2019 at 11:24:59PM -0400, Tom Lane wrote:
> Gunther <raj@xxxxxxxx> writes:
> > ExecutorState: 2234123384 total in 266261 blocks; 3782328 free (17244 chunks); 2230341056 used
>
> Oooh, that looks like a memory leak right enough. The ExecutorState
> should not get that big for any reasonable query.
On Tue, Apr 16, 2019 at 11:30:19AM -0400, Tom Lane wrote:
> Hmm ... this matches up with a vague thought I had that for some reason
> the hash join might be spawning a huge number of separate batches.
> Each batch would have a couple of files with associated in-memory
> state including an 8K I/O buffer, so you could account for the
On Tue, Apr 16, 2019 at 10:24:53PM -0400, Gunther wrote:
> -> Hash (cost=2861845.87..2861845.87 rows=34619 width=74) (actual time=199792.446..199792.446 rows=113478127 loops=1)
> Buckets: 65536 (originally 65536) Batches: 131072 (originally 2) Memory Usage: 189207kB
Is it significant that there are ~2x as many ExecutorState blocks as there are
batches ? 266261/131072 => 2.03...
If there was 1 blocks leaked when batch=2, and 2 blocks leaked when batch=4,
and 4 blocks leaked when batch=131072, then when batch=16, there'd be 64k
leaked blocks, and 131072 total blocks.
I'm guessing Tom probably already thought of this, but:
2230341056/266261 => ~8376
which is pretty close to the 8kB I/O buffer you were talking about (if the
number of same-sized buffers much greater than other allocations).
If Tom thinks (as I understand) that the issue is *not* a memory leak, but out
of control increasing of nbatches, and failure to account for their size...then
this patch might help.
The number of batches is increased to avoid exceeding work_mem. With very low
work_mem (or very larger number of tuples hashed), it'll try to use a large
number of batches. At some point the memory used by BatchFiles structure
(increasing by powers of two) itself exceeds work_mem.
With larger work_mem, there's less need for more batches. So the number of
batches used for small work_mem needs to be constrained, either based on
work_mem, or at all.
With my patch, the number of batches is nonlinear WRT work_mem, and reaches a
maximum for moderately small work_mem. The goal is to choose the optimal
number of batches to minimize the degree to which work_mem is exceeded.
Justin
diff --git a/src/backend/executor/nodeHash.c b/src/backend/executor/nodeHash.c
index 64eec91..4e99093 100644
--- a/src/backend/executor/nodeHash.c
+++ b/src/backend/executor/nodeHash.c
@@ -1036,8 +1036,11 @@ ExecHashIncreaseNumBatches(HashJoinTable hashtable)
* Increasing nbatch will not fix it since there's no way to subdivide the
* group any more finely. We have to just gut it out and hope the server
* has enough RAM.
+ * Also avoid increasing nbatch if an additional nbatch would cause
+ * overhead of batchFiles alone to exceed work_mem.
*/
if (nfreed == 0 || nfreed == ninmemory)
+ // && (1<<hashtable->nbatch > hashtable->spaceAllowed/8192))
{
hashtable->growEnabled = false;
#ifdef HJDEBUG
@@ -1655,8 +1658,18 @@ ExecHashTableInsert(HashJoinTable hashtable,
hashtable->spacePeak = hashtable->spaceUsed;
if (hashtable->spaceUsed +
hashtable->nbuckets_optimal * sizeof(HashJoinTuple)
- > hashtable->spaceAllowed)
- ExecHashIncreaseNumBatches(hashtable);
+ > hashtable->spaceAllowed && hashtable->growEnabled) {
+ /*
+ * spaceUsed doesn't include the overhead of
+ * BatchFile structure. If the overhead of an
+ * additional 2x batch files would use more than the
+ * space itself, do not grow...
+ */
+ if (1<<hashtable->nbatch < hashtable->spaceUsed/8192)
+ ExecHashIncreaseNumBatches(hashtable);
+ else
+ hashtable->growEnabled = false;
+ }
}
else
{
