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Presto (2015)
Past, Present, and Future
SELECT now() - INTERVAL ’10’ MONTH
By The Numbers
▪10 months
▪30 releases (0.68 to 0.98)
▪42 contributors (57 total)
▪1761 commits (4583 total)
▪2406 files changed
▪198,680 insertions(+) 96,833 deletions(-)
Presto@Facebook
▪Scan PBs of data every day
▪Execute millions of queries each month
▪Process trillions rows a day
▪1000s of internal daily active users
New SQL Features
▪Structural types (array, map, row)
▪UNNEST (like Hive’s LATERAL VIEW)
▪Views
▪Aggregate window functions (rolling avg)
▪Tons of new functions (HLL, ML, etc)
▪Session properties
Hive
▪ORC, DWRF and Parquet
▪Real structural types
▪DATE type
▪Null partition keys
▪Improved partition pruning
New Connectors
▪Kafka
▪JDBC (not sharded)
▪MySQL
▪Postgres
▪Generic JDBC
Internal Changes
▪New query queueing system
▪Upgrade to Java 8
▪New ANTLR4 parser
▪New Bytecode compiler framework
▪New aggregation and window framework
▪Partition aware planner
▪IPv6 support (verified)
Optimizations
▪New ORC reader
▪Columnar reads, push down, and lazy
▪Reuse hash calculation across operators
▪Better work load balancing
▪Add “Big Query” support
▪Use partition metadata for simple queries
▪More parallel table writing
Optimizations
▪Wall and CPU efficiency improvements
▪50% for complex queries (joins, etc)
▪300% for simple queries (scan, filter, agg)
▪ORC Data
▪2-4x wall and CPU time speedup
▪4x+ speedup with lazy reads
▪30x+ speedup with predicate push down
2014 Roadmap Checkin
Structural types
Create partition
Distributed joins
Huge joins
Task recovery
Work stealing
Native store
Security
Native ODBC
Plugin repository
Full pushdown
Optimizer plugins
SELECT now()
Reliability
▪Presto resource leaks
▪External bugs (Jetty, JVM)
▪Obscure Presto bugs
▪“G1 friendly” memory allocations
▪Avoid “humongous” allocations
▪Eliminated full GCs
Resource Management
▪New queueing system
▪Full global resource tracking
▪Per query limits -- not per task
▪Block queries until memory is available
Raptor
▪Initial use cases
▪Near real-time loads (every 5-15 minutes)
▪3 TB/day, 80B rows/day
▪5 second query over 1 day of data
▪Stores data in flash on worker nodes
▪Metadata is stored in MySQL
Physical Aware Planner
▪Multiple physical table layouts
▪SPI changes
▪Clustering and partitioning
▪Simplify physically organized connectors
▪Grouping (clustering) aware planning
▪New physical aware operators
Security
▪Authentication
▪Single sign-on: Kerberos or SSL client cert
▪Authorization
▪Simple allow/deny check
SELECT now() + INTERVAL ‘1’ YEAR
APPROXIMATE AT 95.0 CONFIDENCE
SELECT now() + INTERVAL ‘1’ YEAR
APPROXIMATE AT 95.0 CONFIDENCE
33.0
Resource Management
▪Automatic query scaling (no “Big Query”)
▪Better resource control
▪Resource take back
▪Bursting
▪Add and remove “extra” resources
New Planner
▪Search/exploration
▪“Cost-based”
▪Better modeling of:
▪Correlated subqueries
▪Nested loops
▪Connectors can participate
Security
▪Authentication
▪Pluggable backends (LDAP, Kerberos, etc)
▪Authorization
▪Pluggable backends (LDAP, JDBC, etc)
▪Integration with plugins
▪Grant permissions from SQL
Execution Engine
▪Result set caching support
▪Adaptive execution
▪Dictionary aware execution
▪Columnar structural types
▪Failure recovery
▪Draining (possibly work stealing)
SQL Features
▪Types with scale, precision, and length
▪varchar, char, varbinary, binary, decimal
▪Full DDL support
▪CREATE, ALTER, DROP
▪CUBE and ROLLUP
▪Scalar and correlated subqueries (EXISTS)
Raptor
▪Full production rollout
▪Background storage optimization
▪Multiple table layouts
▪Indexes
▪Real time loading
▪UPDATE queries
Other
▪Open source more internal connectors
▪Sharded MySQL
▪Generic Thrift
SELECT question
FROM audience
WHERE is_awesome(question)
(c) 2007 Facebook, Inc. or its licensors.  "Facebook" is a registered trademark of Facebook, Inc.. All rights reserved. 1.0

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