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Fast TSDB backend for graphite

Project description

travis coverage pyver

Time series database, backend for graphite, fast alternative to carbon + whisper.

Features:

  • Low disk usage (IOPS) for metric store, it depends from actual data volumes instead of a number of metrics (in case of whisper). Hisser was designed to process million of metrics.
  • Fast queries. Optimized query parsing and response rendering (~3x boost comparing with vanilla graphite-web).
  • Tag support.
  • Drop-in replacement for whisper + carbon.
  • 100% test coverage.

Table of Contents

Configuration

Default options and documentation for them can be read in default config.

You can create custom configuration file and use --config cli option or use HISSER_* environment variables to override default values. For example HISSER_DATA_DIR will set DATA_DIR configuration parameter.

Run

Simplest way is to use official docker image:

docker run --rm -u $(id -u):$(id -g) -p 2003:2003 -p 8080:8080 -v /path/to/data:/data baverman/graphite-hisser

Port 2003 is a graphite protocol. 8080 is graphite API, you can point grafana to it. In production you don’t need 8080 port accessible from external network. In this case you should use separate docker network and map 2003 port only or use --network host and specify GRAPHITE_BIND=127.0.0.1:8080 envvar.

IMPORTANT! To use tag support with grafana you need grafana 5.x and set graphite version 1.1.x in storage settings.

Note: for grafana you can use tiny grafana image.

Internals

Hisser is a very simple metric storage. All heavy work is done by lmdb. Metrics are organized into blocks (lmdb databases). Each block contains all metrics and their data for particular amount of time. Blocks with same resolution are grouped under corresponding directory:

Example data layout:

data_dir/
├── 300  # resolution (1 data point every 5-minute)
│   ├── 1533990300.519.hdb   # timestamp-of-block-start.number-of-points.hdb
│   ├── 1534621800.191.hdb
│   ├── 1534679100.48.hdb
│   └── blocks.state         # lock file
├── 60   # resolution (1 data point every minute)
│   ├── 1534621920.700.hdb
│   ├── 1534663920.320.hdb
│   ├── 1534683120.160.hdb
│   ├── 1534692720.40.hdb
│   ├── 1534695120.11.hdb
│   ├── 1534695900.6.hdb
│   └── blocks.state
└── metric.index       # metric name and tag index

This layout allows to dump data from memory buffer very efficiently (whisper needs one io-operation per metric and can kneel a host with several hundreds of metrics).

If points in memory exceed BUFFER_FLUSH_SIZE or BUFFER_MAX_POINTS it will be flushed into separate block:

+----------+----------+----------+
|  block1  |  block2  |  block3  |  resolution 60
+----------+----------+----------+

From time to time small blocks are merged into greater one:

+---------------------+----------+
|       block12       |  block3  |  resolution 60
+---------------------+----------+

And from time to time big blocks are downsampled into blocks with lower resolution:

+---------------------+----------+
|       block12       |  block3  |  resolution 60
+---------------------+----------+
           |
           v
     +----------+
     | block12' |  resolution 300
     +----------+

Yes, it is very simple.

FAQ

  1. But there is a better alternative to whisper. InfluxDB!

    Yes, InfluxDB is a way better than whisper. But is has some drawbacks comparing to hisser.

    • Requires more data space.
    • Consumes more IOPS, memory and CPU.
    • Needs manual retention configuration.
    • Slower to query.
    • Implicit metric grouping can lead to confusing graphs in grafana. You have to limit groups to explicit tag values or do group by $tag.

Project details


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Filename, size & hash SHA256 hash help File type Python version Upload date
hisser-0.10.1.tar.gz (18.6 kB) Copy SHA256 hash SHA256 Source None Aug 20, 2018

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