Installing and Running Sequins
You can download a recent release from the github releases page.
Unzip it wherever you like. Then you can run it to see the usage:
$ ./sequins --help usage: sequins [<flags>] Flags: --help Show context-sensitive help (also try --help-long and --help-man). -b, --bind=ADDRESS Address to bind to. Overrides the config option of the same name. -r, --source=URI Where the sequencefiles are. Overrides the config option of the same name. -l, --local-store=PATH Where to store local data. Overrides the config option of the same name. --config=PATH The config file to use. By default, either sequins.conf in the local directory or /etc/ sequins.conf will be used. --debug-bind=ADDRESS Address to bind to for pprof and expvars. Overrides the config option of the same name. --version Show application version.
First, start up sequins and point it to wherever you intend to keep your data. This can be in HDFS:
$ hadoop fs -mkdir /sequins $ ./sequins --local-store /tmp/sequins --bind localhost:9599 \ --source hdfs://namenode:8020/sequins
Or, if you put it in S3, use a S3 URI1:
$ ./sequins --local-store /tmp/sequins --bind localhost:9599 \ --source s3://my-bucket/sequins
If you're just playing around and don't have HDFS or S3 available, you can give sequins a local path:
$ mkdir /tmp/foobar $ ./sequins --local-store /tmp/sequins --bind localhost:9599 \ --source /tmp/foobar
Now you can query it (I'm using httpie here, but curl works just as well):
$ http localhost:9590/foo/bar HTTP/1.1 404 Not Found Content-Length: 0 Content-Type: text/plain; charset=utf-8 Date: Mon, 01 Aug 2016 11:57:53 GMT
However, you'll only get 404s, since sequins hasn't loaded any data yet. We need to give it some.
Writing some data
Sequins works by asynchronously mirroring data at rest in HDFS, S3, or another filesystem. It's particularly suited for ingesting data written from Hadoop or similar tools.
You'll want to write a job that dumps out some key/value-oriented data in the SequenceFile format. This is a commonly-used format in the Hadoop ecosystem, so tools like Pig, Scalding or Spark should all be able to write it out of the box. More info on the supported formats can be found in the Data Requirements section.
Once you have your data ready, you need to arrange it in a particular way in S3, HDFS, or on local disk2:
/path/to/data └── mydata └── version0 ├── part-00000 # These names are irrelevant, but this is how Hadoop ├── part-00001 # names files. ├── part-00002 └── ...
mydata is a name for your dataset, which we'll henceforth call a database.
version0 is the version of the database; that comes into play when we want
to update it. Both are arbitrary strings.
Once your data is written, tell sequins to reload the data by HUPing it:
$ pkill -HUP -f sequins
Sequins should start automatically downloading and mirroring your data. If it's a large dataset, this can take a while. (If it's a really big dataset, you'll want to read about sharding over multiple machines.)
You can check the progress by opening http://localhost:9599 in a browser, or simply watching the logs.
Once your data is finished loading, you can query it by issuing an HTTP GET to
$ http localhost:9599/<database>/<key> HTTP/1.1 200 OK Content-Length: 7 Date: Mon, 01 Aug 2016 11:57:53 GMT Last-Modified: Mon, 01 Aug 2016 11:56:27 GMT X-Sequins-Version: version0 <value>
Sequins usually reads its config from a configuration file called
sequins.conf, either in the local directory or at
The release tarballs contain a
sequins.conf.example, which you can copy and
modify as you please; you can also check out the Configuration
Reference for more details.
1. You may need S3 credentials in your environment or in a config file. See the Configuration Reference. ↩
2. Yes, S3 doesn't have directories. We do our best to pretend that it does, though. More information can be found in the next section. ↩