This document outlines a technical talk on Presto, a distributed SQL query engine that provides ANSI SQL access to various data sources like Hadoop and Kafka. It highlights Presto's scalable architecture, flexible connectors, and performance benefits, along with its use cases and query lifecycle. The document also discusses community engagement and resources for further learning about Presto.

1. Level 101 for Presto
SQL on Everything
Part 1 of the Tech Talk Series for Presto
What is PrestoDB?
What’s the difference?Beinan Wang
Sr. Software Engineer, Twitter
Dipti Borkar
Co-Founder & CPO, Ahana

2. Presto 101 Outline
● What is Presto?
● How are we using Presto?
● What made Presto different?
○ Scalable architecture
○ Flexible Connectors
○ Performance
● The life of a query
2

3. What is Presto?
● Distributed SQL query engine
○ ANSI SQL on Hadoop, Kafka, Druid etc.
○ Designed to be interactive
○ Access to petabytes of data
● Opensource, hosted on github
○ https://github.com/prestodb
● Open question:
○ Is presto a database?
3

4. How are we using Presto?
● Adhoc
● BI tools
● Dashboard
● A/B testing
● ETL/scheduled job
● Online service *
4

5. What made presto different?
● Scalable architecture
● Pluggable Connectors
● Performance
5

6. Scalable architecture
● Two roles -- coordinator and worker
● Easy scale up and scale down
○ Scale up to 1000 workers*
○ Fit in web scaled companies
6

7. Pluggable Presto Connectors

8. Presto Connector Data Model
● Connector: Driver for a data source.
○ Example: HDFS, Cassandra, Kafka, SQL Server
● Catalog: Contains schemas from a datasource specified by the connector
● Schemas: Namespace to organize tables.
● Tables: Set of unordered rows organized into columns with types.
8

9. Presto Hive Connector
9

10. Presto Hive Connector -- Access Control
10

11. Presto Hive Connector -- Data File Types
11
● Supported File Types
○ ORC
○ Parquet
○ Avro
○ RCFile
○ SequenceFile
○ JSON
○ Text
● No data ingestion needed

12. Presto Druid Connector
12

13. Why Presto is Fast
● In-Memory processing
● Pull model
● Columnar storage and execution
● Bytecode generation
13

14. The Life of a Query -- Simple Scan
SELECT *
FROM orders
WHERE discount = 0

15. The Life of a Query -- Join and Aggregation
SELECT
orders.orderkey, SUM(tax)
FROM orders
LEFT JOIN lineitem
ON orders.orderkey = lineitem.orderkey
WHERE discount = 0
GROUP BY orders.orderkey
This example is from Presto: SQL on Everything https://research.fb.com/publications/presto-sql-on-everything/

16. Logical Plan -- do NOT join two big tables
This example is from Presto: SQL on Everything https://research.fb.com/publications/presto-sql-on-everything/

17. Limitations
● Memory Limitation
● Fault Tolerance
● Single Point of Failure: Coordinator
17

18. Time for a demo!
Local Setup
Query TPC-DS
Cloud Setup
Query S3 / Parquet

19. Docker Sandbox for Presto
https://hub.docker.com/r/ahanaio/prestodb-sandbox

20. AWS Sandbox AMI for Presto
https://ahana.io/tutorials/aws-sandbox/

21. Q&A

22. Join the Presto Community
● Require new feature or file a bug: github.com/prestodb/presto
● Slack: prestodb.slack.com
● Twitter: @prestodb
22
Stay up-to-date with Ahana
● URL: ahana.io
● Twitter: @ahanaio