node-memwatch
: Leak Detection and Heap Diffing for Node.JS
node-memwatch
is here to help you detect and find memory leaks in
Node.JS code. It provides:
-
A leak
event, emitted when it appears your code is leaking memory.
-
A stats
event, emitted occasionally, giving you
data describing your heap usage and trends over time.
-
A HeapDiff
class that lets you compare the state of your heap between
two points in time, telling you what has been allocated, and what
has been released.
Installation
or
git clone git://github.com/marcominetti/node-memwatch.git
Description
There are a growing number of tools for debugging and profiling memory
usage in Node.JS applications, but there is still a need for a
platform-independent native module that requires no special
instrumentation. This module attempts to satisfy that need.
To get started, import node-memwatch
like so:
var memwatch = require('memwatch-next');
Leak Detection
You can then subscribe to leak
events. A leak
event will be
emitted when your heap usage has increased for five consecutive
garbage collections:
memwatch.on('leak', function(info) { ... });
The info
object will look something like:
{ start: Fri, 29 Jun 2012 14:12:13 GMT,
end: Fri, 29 Jun 2012 14:12:33 GMT,
growth: 67984,
reason: 'heap growth over 5 consecutive GCs (20s) - 11.67 mb/hr' }
Heap Usage
The best way to evaluate your memory footprint is to look at heap
usage right aver V8 performs garbage collection. memwatch
does
exactly this - it checks heap usage only after GC to give you a stable
baseline of your actual memory usage.
When V8 performs a garbage collection (technically, we're talking
about a full GC with heap compaction), memwatch
will emit a stats
event.
memwatch.on('stats', function(stats) { ... });
The stats
data will look something like this:
{
"num_full_gc": 17,
"num_inc_gc": 8,
"heap_compactions": 8,
"estimated_base": 2592568,
"current_base": 2592568,
"min": 2499912,
"max": 2592568,
"usage_trend": 0
}
estimated_base
and usage_trend
are tracked over time. If usage
trend is consistently positive, it indicates that your base heap size
is continuously growing and you might have a leak.
V8 has its own idea of when it's best to perform a GC, and under a
heavy load, it may defer this action for some time. To aid in
speedier debugging, memwatch
provides a gc()
method to force V8 to
do a full GC and heap compaction.
Heap Diffing
So far we have seen how memwatch
can aid in leak detection. For
leak isolation, it provides a HeapDiff
class that takes two snapshots
and computes a diff between them. For example:
var hd = new memwatch.HeapDiff();
var diff = hd.end();
The contents of diff
will look something like:
{
"before": { "nodes": 11625, "size_bytes": 1869904, "size": "1.78 mb" },
"after": { "nodes": 21435, "size_bytes": 2119136, "size": "2.02 mb" },
"change": { "size_bytes": 249232, "size": "243.39 kb", "freed_nodes": 197,
"allocated_nodes": 10007,
"details": [
{ "what": "String",
"size_bytes": -2120, "size": "-2.07 kb", "+": 3, "-": 62
},
{ "what": "Array",
"size_bytes": 66687, "size": "65.13 kb", "+": 4, "-": 78
},
{ "what": "LeakingClass",
"size_bytes": 239952, "size": "234.33 kb", "+": 9998, "-": 0
}
]
}
The diff shows that during the sample period, the total number of
allocated String
and Array
classes decreased, but Leaking Class
grew by 9998 allocations. Hmmm.
You can use HeapDiff
in your on('stats')
callback; even though it
takes a memory snapshot, which triggers a V8 GC, it will not trigger
the stats
event itself. Because that would be silly.
Future Work
Please see the Issues to share suggestions and contribute!
License
http://wtfpl.org