write-once key/value storage engine
Clojure Java Shell
Latest commit f102db1 May 31, 2016 @bfs bfs Merge pull request #1 from lopusz/master
Exposing chunk-size as a parameter to write-riffle


Riffle is a read-only key/value storage format, strongly influenced by the cdb and sorted-string table formats. Like cdb, it has a fixed memory cost per key (12 bytes per key), rather than having to keep the entire keyspace in memory. Like sorted-string tables, it allows for block compression of the values, and allows for files to be merged in linear time. Like both formats, a typical lookup requires a single disk read.

Riffle files can be built either locally or via Hadoop, allowing for datasets comprising billions of entries to be compiled into a set of sharded Riffle files.

getting started

To use Riffle in your project, add this to your project.clj:

[factual/riffle "0.1.3"]

To use the riffle command-line tool, clone the Riffle repository, make sure Leiningen is installed, and then install the tool:

cd /tmp
git clone https://github.com/Factual/riffle.git
cd riffle
./scripts/install.sh DIRECTORY

where DIRECTORY is a directory on your working $PATH. Now you can use the riffle tool to build, read, validate and benchmark files.

Let's build a small Riffle file using a TSV key/value file:

echo -e "1\t2\n\3\t4\n" | riffle build > /tmp/riffle

This is equivalent to the map {"1" "2", "3" "4"}. Now we can do simple things like list the keys in the file, and look up values:

> riffle -k /tmp/riffle

> riffle -g 3 /tmp/riffle

We can pass in an arbitrary number of Riffle files, in which case the right-most files will take precedence:

> echo -e "3\t5" | riffle build > /tmp/riffle2

> riffle -k /tmp/riffle /tmp/riffle2

> riffle -g 3 /tmp/riffle /tmp/riffle2

> riffle -g 3 /tmp/riffle2 /tmp/riffle

We can also arbitrarily combine TSV and Riffle files to create new Riffle files.

> echo -e "1\t42" > /tmp/input.tsv

> riffle build /tmp/riffle /tmp/riffle2 /tmp/input.tsv > /tmp/riffle3

> riffle -g 1 /tmp/riffle3

Riffle stores keys and values as binary data, but for the convenience of the command-line tool all data is treated as plaintext. To build a file with binary data, you can specify that the input is Base64 encoded with the -b flag:

> echo -e "`echo -n hello | base64`\t`echo -n goodbye | base64`" > /tmp/binary.tsv

> riffle build -b /tmp/binary.tsv > /tmp/binary-riffle

> riffle -kb /tmp/binary-riffle

> riffle -k /tmp/binary-riffle

Additional tasks include validate and benchmark

> riffle validate /tmp/binary-riffle
1 block(s), 67.00 average bytes per compressed block
no bad blocks

> riffle benchmark /tmp/binary-riffle
with 1 reader:
throughput: 28456.82 reads/sec
latencies (in ms):
  25.0%  0.03
  50.0%  0.03
  75.0%  0.03
  90.0%  0.04
  95.0%  0.05
  99.0%  0.07
  99.9%  0.19


riffle and hadoop

To compile a Riffle index via Hadoop, you can use riffle hadoop build src1 src2 ... srcN dst, which takes tab-delimited text input files and builds Riffle indices, and riffle hadoop merge src1 src2 ... srcN dst, which takes multiple Riffle indices and merges them together, with precedence given to the right-most index. These commands must be run in a context where the Hadoop environment is already configured.

To build from a source other than tab-delimited files, it's recommended that you customize the mapper for the RiffleBuildJob, which is trivial to modify. Once modified, your custom Hadoop job can be installed via scripts/install.sh, and invoked via the same riffle hadoop ... mechanism.

riffle as a library

To build a Riffle index at runtime, use riffle.write/write-riffle, which takes a sequence of key/value tuples, an output file, and an optional set of parameters.

> (require '[riffle.write :as w] '[riffle.read :as r])
> (write-riffle [["a" "b"] ["c" "d"]] "/tmp/riffle4")
#<File /tmp/riffle4>

This file may be loaded as an index using riffle.read/riffle and accessed via riffle.read/get and riffle.read/entries:

> (def riff (r/riffle "/tmp/riffle4"))
> (r/get riff "a")
#<byte[] [B@6a2361b0>

Notice that get returns a binary representation of the value.


Copyright © 2014 Factual, Inc

Distributed under the Eclipse Public License v1.0