Meetup my sql5.6_cluster

MySQL 5.6 and Cluster
Lee Stigile – Technical Sales Consulting
Manager -- Americas

1

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

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

2


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

3


MySQL Enterprise Edition
Highest Levels of Security, Performance, and Availability
Oracle Premier
Lifetime Support

MySQL Enterprise
Thread Pool
MySQL Enterprise
Authentication
MySQL Enterprise
Audit

4


MySQL Enterprise
Monitor/Query Analyzer
MySQL Enterprise
Backup

MySQL
Workbench

Features

 Performance
 Online Schema (DDL) Changes

 Replication

 Pre-load Buffer Pool

 Performance Schema

 Full Text Search (InnoDB)

 Partitioning

 NoSQL and SQL Access

5

 Optimizer Improvements

 Compression


#1 Performance

6


MySQL 5.6: Scalability

 Users can fully utilize latest generations of hardware and OS
 Scales as data volumes and users grow
7


MySQL Scalability

January 2010
Oracle Buys Sun
InnoDB joins MySQL

Oracle Buys
Innobase/InnoDB

2005

2008

4 CPU MySQL 5.0

8


2009

4 CPU MySQL 5.1
16 CPU InnoDB Plugin
Sun Micro

2010

2010

December
32 CPU MySQL 5.5

2012

Up to 48 CPU
MySQL 5.6

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)
9


ScienceLogic
Moved from 5.1 to 5.5, 5.6

 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”

10


#2 Online Operations

11


Insert Information Protection Policy Classification from Slide 12

Online DDL for InnoDB Tables
ADD INDEX
DROP INDEX
DROP COLUMN
ADD COLUMN
RENAME COLUMN

12


#3 Optimizer

13


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;

14


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;

15


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

16


#4 Performance Schema

17


MySQL 5.6 – Performance Schema
• Resource-intensive queries
• Tables/indexes with most load
• Users consuming the most resources
• Network load
• Aggregated statistics by
• thread
• user
• host
• object

18


Show which Queries executed the most # of times

19


Top Files by Total I/O (ps_helper)

20


Statements with Temporary Tables

21


MySQL Query Analyzer

22


#5 Replication

23


MySQL 5.6: Crash-Safe Slaves
Atomic

Before:
–

Transaction Data: in tables

–

Replication Info:

Data

CRASH!
Position Info

Time

in files

MySQL 5.6
–
–

24

Transaction Data: in tables
Replication Info: in tables


Atomic

Data
Position Info

Time

Multi-Threaded Slaves
Multi-Threaded Slave Performance

 Reduce Slave Latency
 Per Schema
 Threads per Schema
 Multi-tenancy

300
Queries per Second

 5x Performance Gain

250
200
150
100
50
0
QPS

25


0
58.11

5
144.4
Worker Threads

10
282.53

Honorable Mentions

26


Partitioning
table

partitioned
table

index

SELECT * FROM table
WHERE custID=100

0-99

100-199

200-299

27


index

Compression
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
28


Features

 Performance
 Online Schema (DDL) Changes

 Replication

 Pre-load Buffer Pool

 Performance Schema

 Full Text Search (InnoDB)

 Partitioning

 NoSQL and SQL Access

29

 Optimizer Improvements

 Compression


MySQL Cluster

30



MySQL Cluster – Basic Architecture
•
•
•
•

Active/Active
99.999% Availability
No Single Point of Failure
1 billion/minute
Data Node2

Data Node 1
F1

F2

F2

F1

Data Nodes
31


MySQL Cluster -- Extended

Node Group 2
Node
3

F1

F3

F3
F1

Data Nodes
32


F2

Node
4

Node
2

Cluster
Mgmt

Node
1

Node Group 1

F4

F4

F2

Cluster
Mgmt

Data Node Distribution
F1-Primary

F1-Secondary

F2-Secondary

F2-Primary

Node Group 1

• Four Data Nodes
• Two Replicas
• Two Node Groups
33


F3-Primary

F3-Secondary

F4-Secondary

F4-Primary

Node Group 2

Transparent
• Application
• Transparency
• Sharding

34


Access
Application

1.
2.
3.
4.
5.

Direct API
Key-Value
NoSQL
SQL
Schema-less

HTTP

memcached

JDBC / ODBC / PHP / PERL /
Python / Ruby …

Data Node 1

Data Node2

F1

F2

F2

F1

Data Nodes

35


Flight Control
1. Flight Operations
Management System
2. No Single Point of
Failure

36


ecommerce
1.
2.
3.
4.
5.

37


Payment Processing
Fulfillment
18,000 Retailers
High Availability
Scaling

QUESTIONS?
What’s New in MySQL 5.6

38



Meetup my sql5.6_cluster

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