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Anatomy of
유동민
Presto Anatomy
1. Who

2. What

3. Library

4. Code Generation

5. Plugin

6. Future
Who am I

Who uses Presto
Who am I
ZeroMQ Committer, Presto Contributor
Who am I
49 Contributors

7 Facebook Developer
Who uses Presto
Who uses Presto
http://www.slideshare.net/dain1/presto-meetup-2015

http://www.slideshare.net/NezihYigitbasi/prestoatnetflixhadoopsummit15
@ Facebook / daily
Scan PBs (ORC?)

Trillions Rows

30K Queries

1000s Users
@ Netflix / daily
Scan 15+ PBs (Parquet)

2.5K Queries

300 Users

1 coordinator / r3.4xlarge

220 workers / r3.4xlarge
@ TD / daily
Scan PBs (A Columnar)

Billions Rows

18K Queries

2 coordinators / r3.4xlarge

26 Workers / c3.8xlarge
Who uses Presto - Airbnb
Airpal - a web-based, query execution tool

Presto is amazing. It's an order of magnitude
faster than Hive in most our use cases. It reads
directly from HDFS, so unlike Redshift, there
isn't a lot of ETL before you can use it. It just
works.

- Christopher Gutierrez, Manager of Online Analytics, Airbnb
What is Presto
Presto - Command Line
Presto is
An open source distributed SQL query engine 

for running interactive analytic queries 

against data sources of all sizes 

ranging from gigabytes to petabytes.
http://prestodb.io
Presto is
•Fast !!! (10x faster than Hive)

•Even faster with new Presto ORC reader

•Written in Java with a pluggable backend

•Not SQL-like, but ANSI-SQL

•Code generation like LLVM

•Not only source is open, but open sourced (No private branch)
Presto is
HTTP
HTTP
Presto is
Presto is
CREATE TABLE mysql.hello.order_item AS

SELECT o.*, i.*

FROM hive.world.orders o —― TABLESAMPLE SYSTEM (10)

JOIN mongo.deview.lineitem i —― TABLESAMPLE BERNOULLI (40)

ON o.orderkey = i.orderkey

WHERE conditions..
Coordinator
Presto - Planner
Fragmenter
Worker
SQL Analyzer
Analysis
Logical
Plan
Optimizer
Plan
Plan

Fragment
Distributed
Query

Scheduler
Stage

Execution

Plan
Worker
Worker
Local

Execution

Planner
TASK
TASK
Presto - Page
PAGE
- positionCount
VAR_WIDTH BLOCK
nulls

Offsets
Values
FIEXED_WIDTH BLOCK
nulls
Values
positionCount blockCount 11 F I X E D _ W I D T H po
sitionCount bit encoded nullFlags values length
values
14 V A R I A B L E _ W
I D T H positionCount offsets[0] offsets[1] offsets[2…]
offsets[pos-1] offsets[pos] bit encoded nullFlags
values
Page / Block serialization
Presto - Cluster Memory Manager
Coordinator
Worker
Worker
Worker
GET /v1/memory
@Config(“query.max-memory”) = 20G
@Config(“query.max-memory-per-node”) = 1G
@Config(“resources.reserved-system-memory”) = 40% of -Xmx
System

reserved-system-memory
Reserved

max-memory-per-node
General
Task
Block All tasks
Presto - IndexManager
•LRU worker memory Cache

•@Config(task.max-index-memory) = 64M

•Table (List<IndexColumn> columns)

•Good for Key / Constant tables
Presto - Prestogres
https://github.com/treasure-data/prestogres
•Clients to use PostgreSQL protocol
to run queries on Presto

•Modified pgpoll-ii

•No ODBC driver yet

•Supports Tableau, ChartIO and etc
Presto - Security
•Authentication

•Single Sign On - Kerberos, SSL client cert

•Authorization

•Simple allow / deny
Presto - Misc.
• Presto Verifier

• Presto Benchmark Driver 

• Query Queue

• ${USER} and ${SOURCE} based maxConcurrent, maxQueued

• JDBC Driver

• Python / Ruby Presto Client (Treasure Data)

• Presto Metrics (Treasure Data)

• GET /v1/jmx/mbean/{mbean}, /v1/query/{query}, /v1/node/

• Presto Python/Java Event Collector (Treasure Data)

• QueryStart, SpitCompletion, QueryCompletion
23
Library
Slice - Efficient memory accessor
•https://github.com/airlift/slice

•ByteBuffer is slow

•Slices.allocate(size), Slices.allocateDirect(size)

•Slices.wrappedBuffer(byteBuffer)

•sun.misc.Unsafe

•Address

•((DirectBuffer) byteBuffer).getAddress()

•unsafe.ARRAY_BYTE_OFFSET + byteBuffer.arrayOffset()

•unsafe.getLong(address), unsafe.getInt(address),

•unsafe.copyMemory(src, address, dst, address)
Airlift - Distributed service framework
•https://github.com/airlift/airlift

•Core of Presto communication

•HTTP

•Bootstrap

•Node discovery

•RESTful API

•Dependency Injection

•Configuration

•Utilities
@Path("/v2/event")

public class EventResource {

@POST

public Response createQuery(EventRequests events) {

…

}

}

public class CollectorMainModule implements ConfigurationAwareModule { 

    @Override 

    public synchronized void configure(Binder binder) { 

        discoveryBinder(binder).bindHttpAnnouncement("collector"); 

        jsonCodecBinder(binder).bindJsonCodec(EventRequest.class); 

        jaxrsBinder(binder).bind(EventResource.class); 

    } 

public static void main(String[] args){

Bootstrap app = new Bootstrap(ImmutableList.of(

new NodeModule(),

new DiscoveryModule(),

new HttpServerModule(),

new JsonModule(), new JaxrsModule(true),

new EventModule(),

new CollectorMainModule()

));

Injector injector = app.strictConfig().initialize();

injector.getInstance(Announcer.class).start();

}

}
ex) https://github.com/miniway/presto-event-collector
Fastutil - Fast Java collection
•FastUtil 6.6.0 turned out to be consistently fast.

•Koloboke is getting second in many tests.

•GS implementation is good enough, but is slower than FastUtil and Koloboke.
http://java-performance.info/hashmap-overview-jdk-fastutil-goldman-sachs-hppc-koloboke-trove-january-2015/
ASM - Bytecode manipulation
package pkg;



public interface SumInterface {

long sum(long value);

}

public class MyClass implements SumInterface {

private long result = 0L;



public MyClass(long value) {

result = value;

}



@Override

public long sum(long value) {

result += value;

return result;

}

}

ClassWriter cw = new ClassWriter(0);

cw.visit(V1_7, ACC_PUBLIC, 

"pkg/MyClass", null, 

"java/lang/Object", 

new String[] { "pkg/SumInterface" });

cw.visitField(ACC_PRIVATE, 

"result", "J", null, new Long(0));



// constructor

MethodVisitor m = cw.visitMethod(ACC_PUBLIC, 

"<init>", "(J)V", null, null);

m.visitCode();



// call super()

m.visitVarInsn(ALOAD, 0); // this

m.visitMethodInsn(INVOKESPECIAL, 

"java/lang/Object", "<init>", “()V",

false);
ASM - Bytecode manipulation (Cont.)
// this.result = value

m.visitVarInsn(ALOAD, 0); // this

m.visitVarInsn(LLOAD, 1 ); // value

m.visitFieldInsn(PUTFIELD, 

"pkg/MyClass", "result", "J");

m.visitInsn(RETURN);

m.visitMaxs(-1, -1).visitEnd();



// public long sum(long value)

m = cw.visitMethod(ACC_PUBLIC , "sum", "(J)J", 

null, null);

m.visitCode();



m.visitVarInsn(ALOAD, 0); // this

m.visitVarInsn(ALOAD, 0); // this

m.visitFieldInsn(GETFIELD,

"pkg/MyClass", "result", "J");

m.visitVarInsn(LLOAD, 1); // value

// this.result + value

m.visitInsn(LADD); 

m.visitFieldInsn(PUTFIELD, 

"pkg/MyClass", "result", "J");



m.visitVarInsn(ALOAD, 0); // this

m.visitFieldInsn(GETFIELD, 

"pkg/MyClass", "result", "J");

m.visitInsn(LRETURN);

m.visitMaxs(-1, -1).visitEnd();



cw.visitEnd();

byte[] bytes = cw.toByteArray();

ClassLoader.defindClass(bytes)
Library - Misc.
•JDK 8u40 +

•Guice - Lightweight dependency injection

•Guava - Replacing Java8 Stream, Optional and Lambda

•ANTLR4 - Parser generator, SQL parser

•Jetty - HTTP Server and Client

•Jackson - JSON

•Jersey - RESTful API
Byte Code Generation

Function Variable Binding
Code Generation
•ASM

•Runtime Java classes and methods generation base on SQL

•30% of performance gain

•Where

•Filter and Projection

•Join Lookup source

•Join Probe

•Order By

•Aggregation
Code Generation - Filter
SELECT * FROM lineitem 

WHERE orderkey = 100 AND quantity = 200
AND
EQ

(#0,100)
EQ

(#1,200)
Logical Planner
class AndOperator extends Operator {

private Operator left = new EqualOperator(#1, 100);

private Operator right = new EqualOperator(#2, 200);

@Override

public boolean evaluate(Cursor cur)

{

if (!left.evaluate(cur)) {

return false;

}

return right.evaluate(cur);

}

}

class EqualOperator extends Operator {

@Override

public boolean evaluate(Cursor c)

{

return cur.getValue(position).equals(value);

}

}
Code Generation - Filter
// invoke MethodHandle( $operator$EQUAL(#0, 100) )

push cursor.getValue(#0)

push 100

$statck = invokeDynamic boostrap(0) $operator$EQUAL      

if (!$stack) { goto end; }

push cursor.getValue(#1)

push 200

$stack = invokeDynamic boostrap(0) $operator$EQUAL      

end:      

return $stack 

@ScalarOperator(EQUAL)

@SqlType(BOOLEAN)

public static boolean equal(@SqlType(BIGINT) long left,

@SqlType(BIGINT) long right){

    return left == right;

}

=> MethodHandle(“$operator$EQUAL(long, long): boolean”)
AND
$op$EQ

(#0,100)
$op$EQ

(#1,200)
Local Execution Planner
Code Generation - Join Lookup Source
SELECT col1, col2, col3 FROM tabA JOIN tabB 

ON tabA.col1 = tabB.colX /* BIGINT */ AND tabA.col2 = tabB.colY /* VARCHAR */
Page
Block(colY)
Block(colX)
PagesIndex
0,0 0,1 0,1023 2,100
Block(colX)
Block(colY)
B(X)
B(Y)
B(X) B(X)
B(Y) B(Y)
addresses
channels
Lookup

Source
JoinProbe
-1
-1
3000
-1
1023
100
-1
PagesHash
- hashRow
- equalsRow
ROW
hash
Found!
Code Generation - PageHash
class PagesHash { 

   List<Type> types = [BIGINT, VARCHAR] 

   List<Integer> hashChannels = [0,1] 

   List<List<Block>> channels = [ 

[BLOCK(colX), BLOCK(colX), ...] , 

              [BLOCK(colY), BLOCK(colY), ...] 

]  

} 

class (Compiled)PageHash { 

     Type type_colX = BIGINT 

     Type type_colY = VARCHAR 

     int hashChannel_colX = 0 

     int hashChannel_colY = 1 

     List<Block> channel_colX = 

[ BLOCK(colX), BLOCK(colX), … ] 

     List<Block> channel_colY = 

[ BLOCK(colY), BLOCK(colY), … ] 

}
Code Generation - PageHash (Cont.)
long hashRow (int position, 

Block[] blocks) { 

int result = 0; 

  for (int i = 0; i < hashChannels.size(); i++) {

int hashChannel = hashChannels.get(i); 

       Type type = types.get(hashChannel); 

            

result = result * 31 + 

type.hash(blocks[i], position); 

    } 

return result; 

} 

long (Compiled)hashRow (int position,

Block[] blocks) { 

        int result = 0; 

        result = result * 31 + 

type_colX.hash(block[0], position); 

        result = result * 31 + 

type_colY.hash(block[1], position); 

        return result; 

}
Code Generation - PageHash (Cont.)
boolean equalsRow (

int leftBlockIndex, int leftPosition, 

int rightPosition, Block[] rightBlocks) { 

    for (int i = 0; i < hashChannels.size(); i++) { 

    int hashChannel = hashChannels.get(i); 

       Type type = types.get(hashChannel); 

Block leftBlock = 

channels.get(hashChannel)

.get(leftBlockIndex); 

       if (!type.equalTo(leftBlock, leftPosition,

  rightBlocks[i], rightPosition)) { 

            return false; 

        } 

    } 

    return true; 

}

boolean (Compiled)equalsRow (

int leftBlockIndex, int leftPosition, 

int rightPosition, Block[] rightBlocks) { 

    Block leftBlock = 

channels_colX.get(leftBlockIndex); 

    if (!type.equalTo(leftBlock, leftPosition, 

rightBlocks[0], rightPosition)) { 

            return false; 

    } 

    leftBlock = 

channels_colY.get(leftBlockIndex); 

    if (!type.equalTo(leftBlock, leftPosition, 

rightBlocks[1], rightPosition)) { 

            return false; 

    } 

    return true; 

}
Method Variable Binding
1. regexp_like(string, pattern) → boolean

2. regexp_like(string, cast(pattern as RegexType))  // OperatorType.CAST 

3. regexp_like(string, new Regex(pattern))

4. MethodHandle handle = MethodHandles.insertArgument(1, new Regex(pattern))

5. handle.invoke (string)
@ScalarOperator(OperatorType.CAST)

@SqlType(“RegExp”)

public static Regex castToRegexp(@SqlType(VARCHAR) Slice pattern){ 

  return new Regex(pattern.getBytes(), 0, pattern.length()); 

} 

@ScalarFunction

@SqlType(BOOLEAN)

public static boolean regexpLike(@SqlType(VARCHAR) Slice source,

@SqlType(“RegExp”) Regex pattern){

    Matcher m = pattern.matcher(source.getBytes());

    int offset = m.search(0, source.length());

    return offset != -1;

}
Plugin - Connector
Plugin
•Hive

•Hadoop 1, Hadoop2, CDH4, CDH 5

•MySQL

•PostgreSQL

•Cassandra

•MongoDB

•Kafka

•Raptor
•Machine Learning

•BlackHole

•JMX

•TPC-H

•Example
Plugin - Raptor
•Storage data in flash on the Presto machines in ORC format

•Metadata is stored in MySQL (Extendable)

•Near real-time loads (5 - 10mins)

•3TB / day, 80B rows/day , 5 secs query

•CREATE VIEW myview AS SELECT …

•DELETE FROM tab WHERE conditions…

•UPDATE (Future)

•Coarse grained Index : min / max value of all columns

•Compaction

•Backup Store (Extendable)
No more ?!
Plugin - How to write
•https://prestodb.io/docs/current/develop/spi-overview.html

•ConnectorFactory

•ConnectorMetadata

•ConnectorSplitManager

•ConnectorHandleResolver

•ConnectorRecordSetProvider (PageSourceProvider)

•ConnectorRecordSinkProvider (PageSinkProvider)

•Add new Type

•Add new Function (A.K.A UDF)
Plugin - MongoDB
•https://github.com/facebook/presto/pull/3337

•5 Non-business days

•Predicate Pushdown

•Add a Type (ObjectId)

•Add UDFs (objectid(), objectid(string))
public class MongoPlugin implements Plugin { 

    @Override 

    public <T> List<T> getServices(Class<T> type) { 

        if (type == ConnectorFactory.class) { 

           return ImmutableList.of(

new MongoConnectorFactory(…)); 

        } else if (type == Type.class) { 

            return ImmutableList.of(OBJECT_ID); 

        } else if (type == FunctionFactory.class) { 

            return ImmutableList.of(

new MongoFunctionFactory(typeManager)); 

        } 

        return ImmutableList.of(); 

    } 

}
Plugin - MongoDB
class MongoFactory implements ConnectorFactory {

@Override

public Connector create(String connectorId) {

Bootstrap app = new Bootstrap(new
MongoClientModule());

return app.initialize()

.getInstance(MongoConnector.class);

}

}

class MongoClientModule implements Module {

@Override

public void configure(Binder binder){

binder.bind(MongoConnector.class)

.in(SINGLETON);

…

configBinder(binder)

.bindConfig(MongoClientConfig.class);

}

}
class MongoConnector implements Connector {

@Inject

public MongoConnector(

MongoSession mongoSession,

MongoMetadata metadata,

MongoSplitManager splitManager,

MongoPageSourceProvider 

pageSourceProvider,

MongoPageSinkProvider 

pageSinkProvider,

MongoHandleResolver 

handleResolver) {

… 

}

}
Plugin - MongoDB UDF
public class MongoFunctionFactory 

        implements FunctionFactory { 

    @Override 

    public List<ParametricFunction> listFunctions() 

    { 

        return new FunctionListBuilder(typeManager) 

                .scalar(ObjectIdFunctions.class) 

                .getFunctions(); 

    } 

} 

public class ObjectIdType 

        extends AbstractVariableWidthType { 

    ObjectIdType OBJECT_ID = new ObjectIdType(); 

    @JsonCreator 

    public ObjectIdType() { 

        super(parseTypeSignature("ObjectId"), 

Slice.class); 

    } 

}
public class ObjectIdFunctions { 

    @ScalarFunction("objectid") 

    @SqlType("ObjectId") 

    public static Slice ObjectId() { 

        return Slices.wrappedBuffer(

new ObjectId().toByteArray()); 

    } 

    @ScalarFunction("objectid") 

    @SqlType("ObjectId") 

    p.s Slice ObjectId(@SqlType(VARCHAR) Slice value) { 

        return Slices.wrappedBuffer(

new ObjectId(value.toStringUtf8()).toByteArray())
    } 

    @ScalarOperator(EQUAL) 

    @SqlType(BOOLEAN) 

    p.s boolean equal(@SqlType("ObjectId") Slice left,

@SqlType("ObjectId") Slice right) { 

        return left.equals(right); 

    } 

}
Future
Presto - Future
•Cost based optimization

•Join Hint (Right table must be smaller)

•Huge Join / Aggregation

•Coordinator High Availability

•Task Recovery

•Work Stealing

•Full Pushdown

•Vectorization

• ODBC Driver (Early 2016, Teradata)

• More security (LDAP, Grant SQL)
SELECT question FROM you
Thank You

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[216]Search Reliability Engineering (부제: 지진에도 흔들리지 않는 네이버 검색시스템)[216]Search Reliability Engineering (부제: 지진에도 흔들리지 않는 네이버 검색시스템)
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[214] Ai Serving Platform: 하루 수 억 건의 인퍼런스를 처리하기 위한 고군분투기
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[214] Ai Serving Platform: 하루 수 억 건의 인퍼런스를 처리하기 위한 고군분투기
 
[213] Fashion Visual Search
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[232] TensorRT를 활용한 딥러닝 Inference 최적화
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[242]컴퓨터 비전을 이용한 실내 지도 자동 업데이트 방법: 딥러닝을 통한 POI 변화 탐지
[242]컴퓨터 비전을 이용한 실내 지도 자동 업데이트 방법: 딥러닝을 통한 POI 변화 탐지[242]컴퓨터 비전을 이용한 실내 지도 자동 업데이트 방법: 딥러닝을 통한 POI 변화 탐지
[242]컴퓨터 비전을 이용한 실내 지도 자동 업데이트 방법: 딥러닝을 통한 POI 변화 탐지
 
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[223]기계독해 QA: 검색인가, NLP인가?
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[245] presto 내부구조 파헤치기

  • 2. Presto Anatomy 1. Who 2. What 3. Library 4. Code Generation 5. Plugin 6. Future
  • 3. Who am I Who uses Presto
  • 4. Who am I ZeroMQ Committer, Presto Contributor
  • 5. Who am I 49 Contributors 7 Facebook Developer
  • 7. Who uses Presto http://www.slideshare.net/dain1/presto-meetup-2015 http://www.slideshare.net/NezihYigitbasi/prestoatnetflixhadoopsummit15 @ Facebook / daily Scan PBs (ORC?) Trillions Rows 30K Queries 1000s Users @ Netflix / daily Scan 15+ PBs (Parquet) 2.5K Queries 300 Users 1 coordinator / r3.4xlarge 220 workers / r3.4xlarge @ TD / daily Scan PBs (A Columnar) Billions Rows 18K Queries 2 coordinators / r3.4xlarge 26 Workers / c3.8xlarge
  • 8. Who uses Presto - Airbnb Airpal - a web-based, query execution tool Presto is amazing. It's an order of magnitude faster than Hive in most our use cases. It reads directly from HDFS, so unlike Redshift, there isn't a lot of ETL before you can use it. It just works. - Christopher Gutierrez, Manager of Online Analytics, Airbnb
  • 12. Presto is •Fast !!! (10x faster than Hive) •Even faster with new Presto ORC reader •Written in Java with a pluggable backend •Not SQL-like, but ANSI-SQL •Code generation like LLVM •Not only source is open, but open sourced (No private branch)
  • 15. Presto is CREATE TABLE mysql.hello.order_item AS SELECT o.*, i.* FROM hive.world.orders o —― TABLESAMPLE SYSTEM (10) JOIN mongo.deview.lineitem i —― TABLESAMPLE BERNOULLI (40) ON o.orderkey = i.orderkey WHERE conditions..
  • 16. Coordinator Presto - Planner Fragmenter Worker SQL Analyzer Analysis Logical Plan Optimizer Plan Plan Fragment Distributed Query Scheduler Stage Execution Plan Worker Worker Local Execution Planner TASK TASK
  • 17. Presto - Page PAGE - positionCount VAR_WIDTH BLOCK nulls Offsets Values FIEXED_WIDTH BLOCK nulls Values positionCount blockCount 11 F I X E D _ W I D T H po sitionCount bit encoded nullFlags values length values 14 V A R I A B L E _ W I D T H positionCount offsets[0] offsets[1] offsets[2…] offsets[pos-1] offsets[pos] bit encoded nullFlags values Page / Block serialization
  • 18. Presto - Cluster Memory Manager Coordinator Worker Worker Worker GET /v1/memory @Config(“query.max-memory”) = 20G @Config(“query.max-memory-per-node”) = 1G @Config(“resources.reserved-system-memory”) = 40% of -Xmx System reserved-system-memory Reserved max-memory-per-node General Task Block All tasks
  • 19. Presto - IndexManager •LRU worker memory Cache •@Config(task.max-index-memory) = 64M •Table (List<IndexColumn> columns) •Good for Key / Constant tables
  • 20. Presto - Prestogres https://github.com/treasure-data/prestogres •Clients to use PostgreSQL protocol to run queries on Presto •Modified pgpoll-ii •No ODBC driver yet •Supports Tableau, ChartIO and etc
  • 21. Presto - Security •Authentication •Single Sign On - Kerberos, SSL client cert •Authorization •Simple allow / deny
  • 22. Presto - Misc. • Presto Verifier • Presto Benchmark Driver • Query Queue • ${USER} and ${SOURCE} based maxConcurrent, maxQueued • JDBC Driver • Python / Ruby Presto Client (Treasure Data) • Presto Metrics (Treasure Data) • GET /v1/jmx/mbean/{mbean}, /v1/query/{query}, /v1/node/ • Presto Python/Java Event Collector (Treasure Data) • QueryStart, SpitCompletion, QueryCompletion
  • 23. 23
  • 25. Slice - Efficient memory accessor •https://github.com/airlift/slice •ByteBuffer is slow •Slices.allocate(size), Slices.allocateDirect(size) •Slices.wrappedBuffer(byteBuffer) •sun.misc.Unsafe •Address •((DirectBuffer) byteBuffer).getAddress() •unsafe.ARRAY_BYTE_OFFSET + byteBuffer.arrayOffset() •unsafe.getLong(address), unsafe.getInt(address), •unsafe.copyMemory(src, address, dst, address)
  • 26. Airlift - Distributed service framework •https://github.com/airlift/airlift •Core of Presto communication •HTTP •Bootstrap •Node discovery •RESTful API •Dependency Injection •Configuration •Utilities @Path("/v2/event") public class EventResource { @POST public Response createQuery(EventRequests events) { … } } public class CollectorMainModule implements ConfigurationAwareModule {     @Override     public synchronized void configure(Binder binder) {         discoveryBinder(binder).bindHttpAnnouncement("collector");         jsonCodecBinder(binder).bindJsonCodec(EventRequest.class);         jaxrsBinder(binder).bind(EventResource.class);     } public static void main(String[] args){ Bootstrap app = new Bootstrap(ImmutableList.of( new NodeModule(), new DiscoveryModule(), new HttpServerModule(), new JsonModule(), new JaxrsModule(true), new EventModule(), new CollectorMainModule() )); Injector injector = app.strictConfig().initialize(); injector.getInstance(Announcer.class).start(); } } ex) https://github.com/miniway/presto-event-collector
  • 27. Fastutil - Fast Java collection •FastUtil 6.6.0 turned out to be consistently fast. •Koloboke is getting second in many tests. •GS implementation is good enough, but is slower than FastUtil and Koloboke. http://java-performance.info/hashmap-overview-jdk-fastutil-goldman-sachs-hppc-koloboke-trove-january-2015/
  • 28. ASM - Bytecode manipulation package pkg;
 
 public interface SumInterface {
 long sum(long value);
 } public class MyClass implements SumInterface {
 private long result = 0L;
 
 public MyClass(long value) {
 result = value;
 }
 
 @Override
 public long sum(long value) {
 result += value;
 return result;
 }
 } ClassWriter cw = new ClassWriter(0);
 cw.visit(V1_7, ACC_PUBLIC, "pkg/MyClass", null, "java/lang/Object", new String[] { "pkg/SumInterface" });
 cw.visitField(ACC_PRIVATE, "result", "J", null, new Long(0));
 
 // constructor
 MethodVisitor m = cw.visitMethod(ACC_PUBLIC, "<init>", "(J)V", null, null);
 m.visitCode(); 
 // call super()
 m.visitVarInsn(ALOAD, 0); // this
 m.visitMethodInsn(INVOKESPECIAL, "java/lang/Object", "<init>", “()V", false);
  • 29. ASM - Bytecode manipulation (Cont.) // this.result = value
 m.visitVarInsn(ALOAD, 0); // this
 m.visitVarInsn(LLOAD, 1 ); // value
 m.visitFieldInsn(PUTFIELD, "pkg/MyClass", "result", "J");
 m.visitInsn(RETURN);
 m.visitMaxs(-1, -1).visitEnd();
 
 // public long sum(long value)
 m = cw.visitMethod(ACC_PUBLIC , "sum", "(J)J", null, null);
 m.visitCode(); 
 m.visitVarInsn(ALOAD, 0); // this
 m.visitVarInsn(ALOAD, 0); // this
 m.visitFieldInsn(GETFIELD, "pkg/MyClass", "result", "J");
 m.visitVarInsn(LLOAD, 1); // value
 // this.result + value
 m.visitInsn(LADD); 
 m.visitFieldInsn(PUTFIELD, "pkg/MyClass", "result", "J");
 
 m.visitVarInsn(ALOAD, 0); // this
 m.visitFieldInsn(GETFIELD, "pkg/MyClass", "result", "J");
 m.visitInsn(LRETURN);
 m.visitMaxs(-1, -1).visitEnd();
 
 cw.visitEnd();
 byte[] bytes = cw.toByteArray(); ClassLoader.defindClass(bytes)
  • 30. Library - Misc. •JDK 8u40 + •Guice - Lightweight dependency injection •Guava - Replacing Java8 Stream, Optional and Lambda •ANTLR4 - Parser generator, SQL parser •Jetty - HTTP Server and Client •Jackson - JSON •Jersey - RESTful API
  • 31. Byte Code Generation Function Variable Binding
  • 32. Code Generation •ASM •Runtime Java classes and methods generation base on SQL •30% of performance gain •Where •Filter and Projection •Join Lookup source •Join Probe •Order By •Aggregation
  • 33. Code Generation - Filter SELECT * FROM lineitem WHERE orderkey = 100 AND quantity = 200 AND EQ (#0,100) EQ (#1,200) Logical Planner class AndOperator extends Operator { private Operator left = new EqualOperator(#1, 100); private Operator right = new EqualOperator(#2, 200); @Override public boolean evaluate(Cursor cur) { if (!left.evaluate(cur)) { return false; } return right.evaluate(cur); } } class EqualOperator extends Operator { @Override public boolean evaluate(Cursor c) { return cur.getValue(position).equals(value); } }
  • 34. Code Generation - Filter // invoke MethodHandle( $operator$EQUAL(#0, 100) ) push cursor.getValue(#0) push 100 $statck = invokeDynamic boostrap(0) $operator$EQUAL      if (!$stack) { goto end; } push cursor.getValue(#1) push 200 $stack = invokeDynamic boostrap(0) $operator$EQUAL      end:       return $stack @ScalarOperator(EQUAL) @SqlType(BOOLEAN) public static boolean equal(@SqlType(BIGINT) long left, @SqlType(BIGINT) long right){     return left == right; } => MethodHandle(“$operator$EQUAL(long, long): boolean”) AND $op$EQ (#0,100) $op$EQ (#1,200) Local Execution Planner
  • 35. Code Generation - Join Lookup Source SELECT col1, col2, col3 FROM tabA JOIN tabB ON tabA.col1 = tabB.colX /* BIGINT */ AND tabA.col2 = tabB.colY /* VARCHAR */ Page Block(colY) Block(colX) PagesIndex 0,0 0,1 0,1023 2,100 Block(colX) Block(colY) B(X) B(Y) B(X) B(X) B(Y) B(Y) addresses channels Lookup Source JoinProbe -1 -1 3000 -1 1023 100 -1 PagesHash - hashRow - equalsRow ROW hash Found!
  • 36. Code Generation - PageHash class PagesHash {    List<Type> types = [BIGINT, VARCHAR]    List<Integer> hashChannels = [0,1]    List<List<Block>> channels = [ [BLOCK(colX), BLOCK(colX), ...] ,               [BLOCK(colY), BLOCK(colY), ...] ]  } class (Compiled)PageHash {      Type type_colX = BIGINT      Type type_colY = VARCHAR      int hashChannel_colX = 0      int hashChannel_colY = 1      List<Block> channel_colX = [ BLOCK(colX), BLOCK(colX), … ]      List<Block> channel_colY = [ BLOCK(colY), BLOCK(colY), … ] }
  • 37. Code Generation - PageHash (Cont.) long hashRow (int position, Block[] blocks) { int result = 0;   for (int i = 0; i < hashChannels.size(); i++) { int hashChannel = hashChannels.get(i);        Type type = types.get(hashChannel);             result = result * 31 +  type.hash(blocks[i], position);     } return result; } long (Compiled)hashRow (int position, Block[] blocks) {         int result = 0;         result = result * 31 + type_colX.hash(block[0], position);         result = result * 31 + type_colY.hash(block[1], position);         return result; }
  • 38. Code Generation - PageHash (Cont.) boolean equalsRow ( int leftBlockIndex, int leftPosition,  int rightPosition, Block[] rightBlocks) {     for (int i = 0; i < hashChannels.size(); i++) {     int hashChannel = hashChannels.get(i);        Type type = types.get(hashChannel); Block leftBlock =  channels.get(hashChannel) .get(leftBlockIndex);        if (!type.equalTo(leftBlock, leftPosition,   rightBlocks[i], rightPosition)) {             return false;         }     }     return true; } boolean (Compiled)equalsRow ( int leftBlockIndex, int leftPosition,  int rightPosition, Block[] rightBlocks) {     Block leftBlock =  channels_colX.get(leftBlockIndex);     if (!type.equalTo(leftBlock, leftPosition,  rightBlocks[0], rightPosition)) {             return false;     }     leftBlock =  channels_colY.get(leftBlockIndex);     if (!type.equalTo(leftBlock, leftPosition,  rightBlocks[1], rightPosition)) {             return false;     }     return true; }
  • 39. Method Variable Binding 1. regexp_like(string, pattern) → boolean 2. regexp_like(string, cast(pattern as RegexType))  // OperatorType.CAST  3. regexp_like(string, new Regex(pattern)) 4. MethodHandle handle = MethodHandles.insertArgument(1, new Regex(pattern)) 5. handle.invoke (string) @ScalarOperator(OperatorType.CAST) @SqlType(“RegExp”) public static Regex castToRegexp(@SqlType(VARCHAR) Slice pattern){   return new Regex(pattern.getBytes(), 0, pattern.length());  } @ScalarFunction @SqlType(BOOLEAN) public static boolean regexpLike(@SqlType(VARCHAR) Slice source, @SqlType(“RegExp”) Regex pattern){     Matcher m = pattern.matcher(source.getBytes());     int offset = m.search(0, source.length());     return offset != -1; }
  • 41. Plugin •Hive •Hadoop 1, Hadoop2, CDH4, CDH 5 •MySQL •PostgreSQL •Cassandra •MongoDB •Kafka •Raptor •Machine Learning •BlackHole •JMX •TPC-H •Example
  • 42. Plugin - Raptor •Storage data in flash on the Presto machines in ORC format •Metadata is stored in MySQL (Extendable) •Near real-time loads (5 - 10mins) •3TB / day, 80B rows/day , 5 secs query •CREATE VIEW myview AS SELECT … •DELETE FROM tab WHERE conditions… •UPDATE (Future) •Coarse grained Index : min / max value of all columns •Compaction •Backup Store (Extendable) No more ?!
  • 43. Plugin - How to write •https://prestodb.io/docs/current/develop/spi-overview.html •ConnectorFactory •ConnectorMetadata •ConnectorSplitManager •ConnectorHandleResolver •ConnectorRecordSetProvider (PageSourceProvider) •ConnectorRecordSinkProvider (PageSinkProvider) •Add new Type •Add new Function (A.K.A UDF)
  • 44. Plugin - MongoDB •https://github.com/facebook/presto/pull/3337 •5 Non-business days •Predicate Pushdown •Add a Type (ObjectId) •Add UDFs (objectid(), objectid(string)) public class MongoPlugin implements Plugin {     @Override     public <T> List<T> getServices(Class<T> type) {         if (type == ConnectorFactory.class) {            return ImmutableList.of( new MongoConnectorFactory(…));         } else if (type == Type.class) {             return ImmutableList.of(OBJECT_ID);         } else if (type == FunctionFactory.class) {             return ImmutableList.of( new MongoFunctionFactory(typeManager));         }         return ImmutableList.of();     } }
  • 45. Plugin - MongoDB class MongoFactory implements ConnectorFactory { @Override public Connector create(String connectorId) { Bootstrap app = new Bootstrap(new MongoClientModule()); return app.initialize() .getInstance(MongoConnector.class); } } class MongoClientModule implements Module { @Override public void configure(Binder binder){ binder.bind(MongoConnector.class) .in(SINGLETON); … configBinder(binder) .bindConfig(MongoClientConfig.class); } } class MongoConnector implements Connector { @Inject public MongoConnector( MongoSession mongoSession, MongoMetadata metadata, MongoSplitManager splitManager, MongoPageSourceProvider pageSourceProvider, MongoPageSinkProvider pageSinkProvider, MongoHandleResolver handleResolver) { … } }
  • 46. Plugin - MongoDB UDF public class MongoFunctionFactory         implements FunctionFactory {     @Override     public List<ParametricFunction> listFunctions()     {         return new FunctionListBuilder(typeManager)                 .scalar(ObjectIdFunctions.class)                 .getFunctions();     } } public class ObjectIdType         extends AbstractVariableWidthType {     ObjectIdType OBJECT_ID = new ObjectIdType();     @JsonCreator     public ObjectIdType() {         super(parseTypeSignature("ObjectId"),  Slice.class);     } } public class ObjectIdFunctions {     @ScalarFunction("objectid")     @SqlType("ObjectId")     public static Slice ObjectId() {         return Slices.wrappedBuffer( new ObjectId().toByteArray());     }     @ScalarFunction("objectid")     @SqlType("ObjectId")     p.s Slice ObjectId(@SqlType(VARCHAR) Slice value) {         return Slices.wrappedBuffer( new ObjectId(value.toStringUtf8()).toByteArray())     }     @ScalarOperator(EQUAL)     @SqlType(BOOLEAN)     p.s boolean equal(@SqlType("ObjectId") Slice left, @SqlType("ObjectId") Slice right) {         return left.equals(right);     } }
  • 48. Presto - Future •Cost based optimization •Join Hint (Right table must be smaller) •Huge Join / Aggregation •Coordinator High Availability •Task Recovery •Work Stealing •Full Pushdown •Vectorization • ODBC Driver (Early 2016, Teradata) • More security (LDAP, Grant SQL)