node-memwatch-sfx

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
------------

- npm install node-memwatch

or

- git clone https://github.com/eduardbcom/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:

``javascript
var memwatch = require('node-memwatch');
`

$3

You can then subscribe to leak events. A leak event will be
emitted when your heap usage has increased for five consecutive
garbage collections:

`javascript
memwatch.on('leak', function(info) { ... });
`

The info object will look something like:

`javascript
{ 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' }
`

$3

The best way to evaluate your memory footprint is to look at heap
usage right after 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.

`javascript
memwatch.on('stats', function(stats) { ... });
`

The stats data will look something like this:

`javascript
{
"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.

$3

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:

`javascript
// Take first snapshot
var hd = new memwatch.HeapDiff();

// do some things ...

// Take the second snapshot and compute the diff
var diff = hd.end();
`

The contents of diff will look something like:

`javascript
{
"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.net