Querying Mongo Without Programming Using Funql

Querying MongoDB without
programming using
FUNQL

FUNQL?
Federated
Unified
Query Language

What does this mean?

Federated - Integrates different independent
stand alone data sources into one coherent
view

Unified – One query for different database
technologies: Relational, Document Oriented,
Object Oriented, Key/Value (yes its possible!)

Query Language – Domain: Filtering, data
transformation, aggregation. Can be executed
interatively. No programming knowledge
required.

When to Use

Ad-Hoc queries

When Map/Reduce is overkill

When you don't want to get lost in $}':“{ syntax

Data integration

Business Intelligence

Pre aggregation

Benefits for Mongo

Easier use of MongoDB and quicker completion of
projects.

Standardizes the heterogeneous NoSQL Market.

Protects customer investments by making MongoDB part
of a larger market.

Enlarges the pool of skilled users.

Learning environment for non-technical users and SQL
users.

Co-existence with relational databases and migration
made easy.

Benefits for developers

Skill applicable to different database systems.

Faster development.

Easy testing and data cleaning.

Larger market for developer skills.

Protects your investment in learning NoSQL.

Fast prototyping.

Example
from collection
where object.subobject.field = $parameter
select field, { nested, fields, … }
group by field, aggregates, sub_groups
where condition // on aggregate //= having
into … // File (json/xml) or other database/collection

From - Where - Select
why it makes a big difference to
SQL's select - from - where

Seemingly unimportant syntactical sugar

But it completely changes the execution model of a
query.

Simplifies it from declarative to data-flow

Each statement is a pipeline, reading data from the
previous statement and passing (modified) data to the
next.

Can easily be executed in parallel.

Not invented here: Pioneered by Microsoft with Linq

Dealing with relational data

The join operation fits into the same model.
from table1
join table2 on table1.id = table2.foreign_id

Is now just an pipeline stage, that adds the data from
table2 into the dataflow.

Tables can come from different systems. E.g one is
from MongoDB, the other from DB2

Join grouped operator – returns a 1-n relationship a a
collection of nested documents.

Nested/Recursive Data Structures

flatten operator transforms a (fixed) nested
structure into one linear table.

enumerate linearizes (walks through) an
arbitrarily deeply nested tree.

group turns a linear structure into a nested
structure.

Funql understands database references. You
can use dot-notation for navigation.

Aggregation

The model allows much more advanced
aggregation operations than SQL

Multi dimensional grouping

Mixing of normal select and aggregation

Analytics directly in the query

Can leverage MongoDBs new aggregation
operators

Funql and the Aggregation
Framework

Both use the same pipeline model

select statement == mongos project

flatten stetement ~~ mongo's unwind

range == first, last

Simple mapping, so Funql can operate at
Mongo's native speed.
db.zips.aggregate({$group:{_id: '$city', pop: {$sum: '$pop'}}}, {$sort: {pop: -1}}})

from zips
group by city, sum pop as pop
sort by pop descending

Status

Formal language spec at
reportsanywhere.com/pebble

Twitter: @reportsanywhere

funql.org is coming up

Reference implementation in Java currently for
 MongoDB
 Generic Json data
 Cassandra (coming)
 Relational Databases (coming)

Fork it on Bitbucket (coming up)

Architecture

Core Engine

Can filter, select, join, sort, group, aggregate

Extremely simple driver API: 5 Methods.
open/close, iterate, lookup, range

Not necessarily optimized

Advanced driver API: Examines the syntax tree
and invokes native operations.

Querying Mongo Without Programming Using Funql

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