Meetup my sql5.6_cluster

Copyright © 2013, Oracle and/or its affiliates. All rights reserved. 1

MySQL 5.6 and Cluster

Lee Stigile – Technical Sales Consulting

Manager -- Americas


Agenda

Goal:

Benefits of Upgrading to MySQL 5.6

Understand MySQL Cluster

MySQL 5.6 – Top 5 New Features

Improved Features: Compression and Partitioning

MySQL Cluster


Oracle Invests Innovations for the MySQL Community Oracle Delivers. Past 12 Months:

GA: MySQL 5.6, MySQL Cluster 7.3, MySQL Workbench 6.0, MySQL

Utilities, MySQL Connectors...and more

DMRs: MySQL 5.7

Labs: Multi-source Replication, Fabric


Oracle Premier Lifetime Support

MySQL Enterprise Authentication

MySQL Enterprise Thread Pool

MySQL Enterprise Backup

MySQL Enterprise Monitor/Query Analyzer

MySQL Enterprise Edition Highest Levels of Security, Performance, and Availability

MySQL Enterprise Audit

MySQL Workbench


Features

Performance

Online Schema (DDL) Changes

Pre-load Buffer Pool

Full Text Search (InnoDB)

NoSQL and SQL Access

Optimizer Improvements

Replication

Performance Schema

Partitioning

Compression


#1 Performance


MySQL 5.6: Scalability

Users can fully utilize latest generations of hardware and OS

Scales as data volumes and users grow


2008 2009 2010 2012

4 CPU MySQL 5.0 4 CPU MySQL 5.1

16 CPU InnoDB Plugin

Sun Micro

December

32 CPU MySQL 5.5

Up to 48 CPU

MySQL 5.6

MySQL Scalability

Oracle Buys

Innobase/InnoDB

2005

January 2010

Oracle Buys Sun

InnoDB joins MySQL

2010


Performance Improvements InnoDB and MySQL

Refactored InnoDB Split kernel mutex

Separate thread for flushing operations

Multi-threaded purge

Reduced buffer pool contention

New adaptive hashing algorithm

MySQL Memory Allocation

Switch from malloc to better memory allocators for multi-threaded

concurrency

Lock_open contention (bottleneck when opening tables)


ScienceLogic

Network Monitoring Software

Averages 8,000 queries every second or about 1 billion queries a day

Can reach 175,000 tables and up to 20 million rows in a single table.

2 terabytes on average

“tremendous performance gains”

“moving log-flushing from a main process to a background process”

Moved from 5.1 to 5.5, 5.6

Copyright © 2012, Oracle and/or its affiliates. All rights reserved. Insert Information Protection Policy Classification from Slide 12 11

#2 Online Operations


Online DDL for InnoDB Tables

ADD INDEX

DROP INDEX

ADD COLUMN

DROP COLUMN

RENAME COLUMN


#3 Optimizer


DBT-3 Benchmarks Open-source Benchmark

DBT1,2,4,5 OLTP, Web Services,

Web Server

DBT-3 Decision Support Systems

Large Data Volume

Complex Queries

QUERY #16

SELECT p_brand, p_type, p_size, count(distinct ps_suppkey)

as supplier_cnt

FROM partsupp, part

WHERE p_partkey = ps_partkey AND p_brand <> 'Brand#23'

AND p_typce not like 'LARGE PLATED%' AND p_size in

(43, cc1, 25, 5, 35, 12, 42, 40)

AND ps_suppkey not in (

SELECT s_suppkey FROM supplier

WHERE s_comment like '%Customer%Complaints%')

GROUP BY p_brand, p_type, p_size

ORDER BY supplier_cnt desc, p_brand, p_type, p_size;


Materialized Subqueries Query #17

~40 days to execute

Now – 6.8 seconds

Executes Once

Hash Index

Query #16 0.65 -> 0.47

QUERY #17

SELECT c_name, c_custkey, o_orderkey, o_orderdate,

o_totalprice, sum(l_quantity)

FROM customer, orders, lineitem

WHERE o_orderkey in (

SELECT l_orderkey

FROM lineitem

GROUP BY l_orderkey

HAVING sum(l_quantity) > 313)

AND c_custkey = o_custkey

AND o_orderkey = l_orderkey

GROUP BY c_name, c_custkey, o_orderkey,

o_orderdate, o_totalprice

ORDER BY o_totalprice desc, o_orderdate

LIMIT 100;


Optimizer Summary Complex

Optimize Many Tables in Join 25+

Postpone Materialization of Views/Subqueries in FROM

Indexes for Derived Tables

Standard Optimize “IN” clause

Optimized SELECT col1, … FROM t1 .. ORDER BY name LIMIT 10

Better Optimizer Diagnostics

EXPLAIN for INSERT, UPDATE and DELETE

EXPLAIN output in JSON


#4 Performance Schema


• Resource-intensive queries

• Tables/indexes with most load

• Users consuming the most resources

• Network load

• Aggregated statistics by

• thread

• user

• host

• object

MySQL 5.6 – Performance Schema


Show which Queries executed the most # of times


Top Files by Total I/O (ps_helper)


Statements with Temporary Tables


MySQL Query Analyzer


#5 Replication


Before:

– Transaction Data: in tables

– Replication Info: in files

MySQL 5.6

– Transaction Data: in tables

– Replication Info: in tables

Data

Position Info

CRASH!

Time

Atomic

Data

Position Info Time

Atomic

MySQL 5.6: Crash-Safe Slaves


0 5 10

QPS 58.11 144.4 282.53

0

50

100

150

200

250

300

Qu

eri

es p

er

Seco

nd

Worker Threads

Multi-Threaded Slave Performance

Multi-Threaded Slaves

5x Performance Gain

Reduce Slave Latency

Per Schema

Threads per Schema

Multi-tenancy


Honorable Mentions


SELECT * FROM table WHERE custID=100

table index table index

0-99

100-199

200-299

partitioned Partitioning


current: Antelope

new: Barracuda

compression off-page storage of variable length data

[mysqld]

innodb_file_format=Barracuda

innodb_file_per_table=1

row_format=compressed

key_block_size=8 # or 4, 2, 1K

Compression


Features

Performance

Online Schema (DDL) Changes

Pre-load Buffer Pool

Full Text Search (InnoDB)

NoSQL and SQL Access

Optimizer Improvements

Replication

Performance Schema

Partitioning

Compression


MySQL Cluster


MySQL Cluster – Basic Architecture

Data Node 1

F1

F2

Data Node2

F2

F1

Data Nodes

• Active/Active

• 99.999% Availability

• No Single Point of Failure

• 1 billion/minute


MySQL Cluster -- Extended

Data Nodes

Node Group 1

F1

F3

F3

F1

No

de

1

No

de

2

Node Group 2

F2

F4

F4

F2

No

de

3

No

de

4

Cluster

Mgmt Cluster

Mgmt


Data Node Distribution

• Four Data Nodes

• Two Replicas

• Two Node Groups

F2-Secondary

F1-Secondary

F2-Primary

Node Group 1

F3-Primary

F4-Secondary

F3-Secondary

F4-Primary

Node Group 2

F1-Primary


Transparent

• Application

• Transparency

• Sharding


Access

memcached HTTP

Data Node 1

F1

F2

Data Node2

F2

F1

Data Nodes

Application

JDBC / ODBC / PHP / PERL /

Python / Ruby …

1. Direct API

2. Key-Value

3. NoSQL

4. SQL

5. Schema-less


Flight Control

1. Flight Operations

Management System

2. No Single Point of

Failure


ecommerce

1. Payment Processing

2. Fulfillment

3. 18,000 Retailers

4. High Availability

5. Scaling


QUESTIONS?

What’s New in MySQL 5.6

Technology

Meetup my sql5.6_cluster