Presto is a distributed SQL query engine optimized for interactive analysis of large datasets across multiple data sources. It aims to improve on Hadoop by allowing data scientists to run queries with low latency. Presto's architecture allows it to distribute queries across a cluster and retrieve data in memory for fast performance. It supports various connectors to data sources like HDFS, Cassandra and Hive. The document outlines Presto's features and performance advantages. It also discusses the open source project's future plans to add more SQL features, improve large joins and aggregations, develop an ODBC driver and potentially introduce a native storage format.

1. Presto
Past, Present and Future
Martin Traverso
June 5, 2014

2. Why build Presto?

3. “A good day is when I
can run 6 Hive queries”
— a Facebook data scientist

4. What is Presto?
Distributed SQL analytics engine
Optimized for low-latency, interactive analysis
ANSI SQL
Extensible

5. Architecture

6. Architecture
Scheduler
Data
Location API
Parser/
Analyzer
Planner
Metadata
API
Coordinator
Client
Worker
Worker
Worker
Data Stream API
Data Stream API

7. Connectors
Coordinator Worker
Parser/
Analyzer
Planner Scheduler
Cassandra
Internal
MySQL
JMX
Hive
Metadata API
Cassandra
Internal
MySQL
JMX
Hive
Data Location API
Cassandra
Internal
MySQL
JMX
Hive
Data Stream API

8. Connectors
Hadoop 1.x
Hadoop 2.x
CDH 4
CDH 5
Custom S3 integration for Hadoop
Cassandra
TPC-H

9. Other extension points
Types
Functions
Operators

10. What makes Presto fast?
Data in memory during execution
Pipelining and streaming
Very careful coding of inner loops
Efficient flat-memory data structures
Bytecode generation

11. What’s next?

12. More SQL features
Structs, Maps and Lists
Views
Scalar sub queries
Features required to run all TPC-DS

13. Execution engine
Huge joins and aggregations
•Hash distributed
•Co-distributed and co-partitioned
•Spill to disk (flash)
Work stealing
Basic task recovery

14. ODBC driver
Targeting major BI tools
•Tableau, MicroStrategy and Excel
Support for Windows, Mac and Linux
Entirely open source (ASL2)

15. Native store
Stores data directly on worker nodes
Custom data format
Initial use cases
•‘Hot’ data
•‘Live’ data

16. Open source
Apache License 2.0
Open development
Releases every 1-2 weeks
!
External contributions welcome!

17. Presto
http://prestodb.io
github.com/facebook/presto
!
Martin Traverso
@mtraverso
github.com/martint

18. Bytecode generation
while (in.advanceNextPosition()) {!
if (in.getLong(3) >= 100 && !
in.getLong(3) <= 200 &&!
in.getLong(4) < in.getLong(5)) {!
!
out.advance();!
in.appendStringTo(0, out);!
out.appendLong(in.getLong(1) * in.getLong(2) / 10);!
}!
}
SELECT!
k AS c1,!
(a * b) / 10 AS c2!
FROM T!
WHERE!
c BETWEEN 100 AND 200!
AND d < e!
T: !
k varchar, !
a bigint, !
b bigint, !
c bigint, !
d bigint, !
e bigint