Quick Start

SociaLite is a parallel/distributed query language. SociaLite queries are embedded in Java programs or Python (Jython) scripts, and compiled to parallel/distributed Java code. The easiest way to learn SociaLite is through the SociaLite interactive shell.

Starting a SociaLite Shell

To start using the SociaLite interactive shell, first install SociaLite and run bin/socialite. To run a script, pass the script name such as bin/socialite script-name.py. The SociaLite interactive shell is a Jython shell extended to support SociaLite queries. Normally the shell expects Python code, and SociaLite queries are enclosed in backtick(`), like following. Click >>> on the top-right to hide the prompts.

>>> print "Python code"
'''Python code'''
>>> # Next two lines are SociaLite code
>>> `Friend(String n, String f).
...  Friend(n, f) :- n="John", f="Tom".`
>>> # Iterating over a table
>>> for n, f in `Friend(n, f)`:
...     print n, f
'''John    Tom'''

The above SociaLite query creates a two-column table Friend, inserts one tuple {"John", "Tom"} into the table, and iterates over the table to print the tuples.


In SociaLite, data is stored in (in-memory) tables, which can be declared as following.

>>> `FriendNum(String name, int num).`

This declares a table FriendNum that has two columns with String and int type. Column types can be primitive types (int, long, float, and double), object types (String, Utf8, and user-defined types), and array types (int[], String[], etc). Notice that table declarations must end with a dot (.).

Tables can have nested structures. Nesting is indicated by parenthesis as in Friend(String i, (String f)). . The nesting must be at the end -- so, Foo(int x, (int y, int z)). is allowed, but Foo(int x, (int y), int z). is not. Multiple nestings are supported as in Foo(int x, (int y, (int z))).

Columns can have options; the followings are some of popular options.

  1. Range option -- e.g. Foo(int i:0..10, (int j:0..20, String f, (int k:0..5))).

    Range option is for columns whose values are within a given ranges. In the example above, the first column of Foo table has values ranging from 0 to 10. Only the first column and first of nested columns can have the range options -- the i,j,k columns in the above. This option allows SociaLite to optimize the columns to be represented as array indices.

  2. Indexby option -- e.g. Bar(String s, double v) indexby s.

    This option adds an index to a given column. The first column of the Bar table in the example is indexed, which can make join operations faster.

  3. Iter option -- e.g. Qux(int n, int i:iter, int v).

    This option is used for a table having values that are updated inside a loop. The option supports fast access to the values at current and previous iterations by storing only the values of last two iterations. For example, the rule Qux(s, 2, x) :- Qux(s, 1, x1), x=x1+42. is executed faster with the option, because Qux table only stores the values of iteration 1 and 2. See PageRank demo for an example.

To iterate elements over a table, you can simply do following

>>> for i, j, f in `Foo(i, j, f)`:
...     print i,j,f

Tables are partitioned, or sharded, by its first column. That is, tables are horizontally partitioned, and the value of the first column of a tuple determines in which partition the tuple is stored. When running on a distributed cluster, the partitions (shards) are stored across the distributed machines.


In SociaLite, programming logic is expressed in rules. An example of a rule is shown in following.

>>> # first, declare tables
>>> `Foaf(String a, String b) indexby a.
...  Friend(String a, String b) indexby a.`
>>> # then, run the following rule
>>> `Foaf(i, ff) :- Friend(i, f), Friend(f, ff).`

In the above rule, the Friend table in the rule body -- right-hand side of :- -- is joined with Friend table itself, and the result is inserted into the Foaf table in the rule head -- left-hand side of :- . More specifically, the term Friend(i,f) iterates each tuple from Friend table, and assigns to variable i, f; for the assigned value of f, matching tuples from Friend table are retrieved and assigned to variable ff, and the result tuple {i, ff} is added to Foaf table. If the Friend table contains three tuples {'a','b'}, {'b','c'}, {'b','d'}, then the following two tuples, {'a','c'} and {'a','d'}, are inserted to Foaf table. In other words, the above rule finds friends-of-friends and store them in the Foaf table.

Selecting particular tuples can be done like following.

>>> `TomsFoaf(String f) indexby f.`
>>> `TomsFoaf(ff) :- Friend("Tom", f), Friend(f, ff).`

Here in Friend("Tom", f), we select only the tuples whose first column value exactly matches "Tom". For each of such tuples, we find matching tuples in Friend(f, ff), and add Tom's friends of friends in TomsFoaf table.

In the following example, Foaf table stores friends as well as friends-of-friends.

>>> `Foaf(i, f) :- Friend(i, f).
...  Foaf(i, ff) :- Friend(i, f), Friend(f, ff).`

The first rule adds tuples from Friend table into Foaf table, and the next rule adds friends-of-friends to Foaf table. Basically the result of the two rules are unioned and stored in Foaf table.

Each rule is evaluated in parallel -- the logical partitions in the first table of the rule body are accessed by multiple cores, which evaluate the rule in parallel.

Functions and Aggregate Functions

SociaLite rules support Python functions. Python functions in rules are prefixed with a dollar ($) sign as in the following example.

>>> @returns(str)
... def getLastName(fullname):
...     f,l = fullname.split(' ')
...     return l
>>> # declare tables
>>> `Friend(String n, String f) indexby n.
...  FriendLastName(String n, String l) indexby n.`
>>> # insert a tuple into Friend table
>>> `Friend(i, f) :- i="Tom Hanks", f="Tom Cruise".`
>>> `FriendLastName(i, l) :- Friend(i, f), l=$getLastName(f).`

In the example, we first defined a function getLastName that returns the last name given a full name. Notice that the function is declared with a decorator returns which declares the type of the return value -- string type, in the above case. Then we declare tables, and insert a tuple {"Tom Hanks", "Tom Cruise"} into the Friend table. The next rule computes friends' last names and stores in the FriendLastName table.

Aggregate functions are also supported as in the following example

>>> @returns(int)
... def incBy(n, inc):
...     return n+inc
>>> `FriendCnt(String n, int cnt) indexby n.`
>>> `FriendCnt(n, $incBy(1)) :- Friend(n, f).`

We define an aggregate function incBy that takes two numbers and returns the sum. Then we declare FriendCnt table that stores the number of friends for each person. In the next rule, we iterate tuples in the Friend table, and increment the friend count for person n by 1. That is, for each tuple {n,f} in the Friend table, SociaLite groups the FriendCnt table by the value of n to get the current friend count of n. The current count is passed to the incBy function along with the arguments specified in the rule -- 1 in the example. The count in the table is updated with the return value of the function, which is the current count incremented by one.

Built-in Functions

SociaLite supports various built-in functions and aggregate functions. Here we list a few of them; for a complete list, please see Documentation.

Function Description
$read("file://path-to-file") returns lines in a given file. e.g. l=$read("file://a.txt") or l=$read("hdfs://graph.txt")
$split("src-str", "delim"[, maxsplit]) returns the splitted string. e.g. (a,b,c)=$split(line, ";")
$splitIter("src-str", "delim") splits the string, and returns the splitted string one by one. e.g. a=$splitIter(line, "\t")
$max(n), $min(n) aggregate function computing max/min
$sum(n) aggregate function that computes the sum

For example, to read comma-separated values in a text file, you can write as following:

>>> `Values(int a, int b).`
>>> `Values(a,b) :- l=read("file://path/to/file.txt"), (v1,v2)=$split(l), a=$toInt(v1), b=$toInt(v2).`

Starting a SociaLite Shell (Cluster)

The SociaLite programs can run on a cluster running SociaLite servers. Setting up a SociaLite cluster is described in install SociaLite. Once the cluster is set up, SociaLite shell can be executed with -d option to connect to the cluster, like bin/socialite -d. To run a script in the cluster, pass the script name like bin/socialite -d script-name.py.

You can run the same script on a single machine or on a distributed cluster. When running on a cluster, SociaLite tables are sharded by its first column and stored across the distributed tables.

Range-based partitioning If a range operator is applied e.g. Foo(int a:0..100, String s)., then tuples having first column values within a certain range are stored in a same partition. For example, for the Foo table, if there are two machines in the cluster, tuples with values from 0 to 50 in the first column are stored in one machine, and the rest tuples are stored in another machine.

Hash-based partitioning If the location operator is used without the range operator, we apply hash-based partitioning where the hash of the first column value is used to determine the location to store a given tuple.

More documentation is coming soon!