Oracle Database In-Memory Meets Oracle RAC

Copyright © 2015, Oracle and/or its affiliates. All rights reserved. |

Oracle Database In-‐Memory Meets Oracle RAC

Markus Michalewicz Senior Director of Product Management Andy Rivenes Senior Principal Product Manager

#DBIM12c


Safe Harbor Statement The following is intended to outline our general product direcQon. It is intended for informaQon purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or funcQonality, and should not be relied upon in making purchasing decisions. The development, release, and Qming of any features or funcQonality described for Oracle’s products remains at the sole discreQon of Oracle.

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What is Database In-‐Memory

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Oracle Database In-‐Memory: Dual Format Database

•  BOTH row and column formats for same table

•  Simultaneously acQve and transacQonally consistent

•  AnalyQcs & reporQng use new in-‐memory column format

•  OLTP uses proven row format

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Normal Buffer Cache

New In-‐Memory Format

SALES SALES Row

Format Column Format

SALES


Oracle In-‐Memory Columnar Technology •  Pure in-‐memory column format

•  Enable for subset of database

•  Cheap to maintain – no logging or IO

•  Allows efficient OLTP

•  No change to disk format

•  Built seamlessly into Oracle Database •  Appears as a new storage type •  Transparent to ApplicaQons •  All Enterprise Features work ..

•  Availability – RAC, Flashback, DataGuard, etc. •  Security – EncrypQon, AudiQng, etc.

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SALES

Pure In-‐Memory Columnar


PopulaQng the In-‐Memory Column Store

•  New INMEMORY ATTRIBUTE

•  Following segment types are eligible

•  Tables

•  (Sub)ParQQons

•  Materialized views

•  Following segment types not eligible

•  IOTs •  Hash clusters

•  Out of line LOBs

ALTER TABLE sales INMEMORY; ALTER TABLE sales NO INMEMORY;

Pure OLTP Features


Why is an In-‐Memory scan faster than the buffer cache?

SELECT COL4 FROM MYTABLE;

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X X X X X

RESULT

Row Format

Buffer Cache


Why is an In-‐Memory scan faster than the buffer cache?

SELECT COL4 FROM MYTABLE;

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RESULT

Column Format

IM Column Store

RESULT

X X X X


How easy is it to get started

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Oracle In-Memory: Simple to Implement

1. Configure Memory Capacity •  inmemory_size = XXX GB

2. Configure tables or partitions to be in memory •  alter table | partition … inmemory;

3.  Later drop analytic indexes to speed up OLTP

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Configuring: New StaQc Area within SGA

System Global Area SGA

Buffer Cache

Shared Pool

Log Buffer

Large Pool

In-‐Memory Area Other

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Configuring : In-‐Memory Column Store

•  Controlled by INMEMORY_SIZE parameter

• Minimum size of 100MB

•  SGA_TARGET must be large enough to accommodate •  StaQc Pool

SELECT * FROM V$SGA; NAME VALUE ------------------ ---------- Fixed Size 2927176 Variable Size 570426808 Database Buffers 4634022912 Redo Buffers 13848576 In-Memory Area 1024483648


Oracle In-Memory Requires Zero Application Changes

Full Func9onality -‐ No restricQons on SQL Easy to Implement -‐ No migraQon of data Fully Compa9ble -‐ All exisQng applicaQons run unchanged Fully Mul9tenant -‐ Oracle In-‐Memory is Cloud Ready

Uniquely Achieves All In-‐Memory Benefits With No Applica9on Changes


How does Database In-‐Memory work with RAC

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The Setup is Basically the Same

1. Configure Memory Capacity •  inmemory_size = XXX GB

2. Configure tables or partitions to be in memory •  alter table | partition … inmemory;

3.  Later drop analytic indexes to speed up OLTP

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Configuring IM Column Stores for RAC – Details Mamer

•  If you can’t avoid spilling to temp do it efficiently -  Increase size of temp writes from 200KB to 1MB -  Set _smm_auto_max_io_size =1024

• Database In-‐Memory is not enabled by default •  INMEMORY_SIZE must be set to 100MB or larger •  SGA_TARGET ExisQng SGA_TARGET INMEMORY_SIZE

• PGA_TARGET PARALLEL_MAX_SERVERS 2GB

(Single Instance) •  SGA_TARGET (ExisQng SGA_TARGET INMEMORY_SIZE) * 1.1 (RAC)

(See MOS Note 1903683.1)


In-‐Memory and DistribuQon of Data in RAC

•  DistribuQon allows in memory segments larger than individual instance memory

•  Policy is automaQc (Distribute AUTO) or user-‐specifiable

•  Controlled by DISTRIBUTE subclause

•  Distribute by rowid range •  Distribute by parQQon •  Distribute by subparQQon

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ALTER TABLE sales INMEMORY DISTRIBUTE BY PARTITION; ALTER TABLE COSTS INMEMORY DISTRIBUTE ROWID RANGE;


ORDERS PARTITION BY HASH ON ORDER_ID

0

1

2

3

4 ….

Scale-‐Out: Distribute by ParQQon

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•  Distribute by ParQQon (top-‐level parQQon for composite parQQoned tables)

•  Ideal for Hash ParQQons

•  Also for other parQQon types if uniformly accessed

•  Allows in-‐memory parQQon-‐wise joins

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ORDERS PARTITION BY RANGE ON ORDER_DATE SUBPARTITION BY HASH ON ORDER_ID

Nov ‘13 1

Nov ‘13 2

Nov ’13 3

Nov ’13 4

Dec ‘13 1 ….

Scale-‐Out: Distribute by Sub-‐ParQQon

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•  For composite parQQons, can distribute by Sub-‐ParQQon

•  Ideal for Hash Sub-‐ParQQons

•  Also for other sub-‐parQQon types if uniformly accessed

•  Allows in-‐memory parQQon-‐wise joins

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ORDERS Rowid Ranges

1-‐105

106-‐201

202-‐310

311-‐421.

422-‐535

….

Scale-‐Out: Distribute by Rowid Range

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•  Distributes IMCUs by uniform hash on first rowid

•  For non-‐parQQoned tables

•  Also for parQQoned tables with skewed access across parQQons

•  Ensures uniform distribuQon of load across instances

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How to get data in and out

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PopulaQon: Priority •  Order in which objects are populated controlled by PRIORITY subclause

-  CriQcal, high, medium, low

-  Default – none (populate on first access)

-  Does not control the speed of populaQon

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PopulaQon: Compression •  Objects compressed during populaQon

•  Controlled by MEMCOMPRESS subclause

•  2x to 20x compression typical

• MulQple levels of compression -  FOR DML

-  FOR QUERY (Default)

-  FOR CAPACITY

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•  Speed of memory •  Scan and Filter only the needed Columns

•  Vector InstrucQons

Improvements to All Aspects of an AnalyQc Query

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Data Scans Ve

ctor Register

Load mulQple region values

Vector Compare all values an 1 cycle

CPU CA

CA CA

CA

In-‐Memory Aggrega9on

• Runs Reports Instantly • Create In-‐Memory Report Outline that is Populated during Fast Scan

Joins

• Convert Star Joins into 10X Faster Column Scans

• Search large table for values that match small table

HASH JOIN

Table A Table B


How does it work on RAC

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Querying Oracle Database In-‐Memory in RAC environment •  Serial queries will only

access a fraction of the data from the IM column store on its node

•  IMCUs not shipped across interconnect

•  Rest of the data comes from disk

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User


Querying Oracle Database In-‐Memory in RAC environment •  Parallel execution helps as it

starts multiple processes

•  BUT we can’t control where the parallel server processes are started

•  IMCUs not shipped across interconnect

•  Remaining data comes from disk

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Enable Auto DOP •  Set parallel_degree_policy = auto

– Enables Auto DOP, statement queuing, in-‐memory PX

•  For Database In-‐Memory it is important, because it – Ensures that at least one parallel server slave is allocated for each database instance

– Ensures that the query coordinator is IMCU home locaQon aware

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Querying Oracle Database In-‐Memory in RAC environment •  Shared nothing architecture

means Auto DOP must be used to access Data

•  With Auto DOP query coordinator is aware of IMCU locations

•  Query coordinator automatically starts parallel server processes on the correct nodes

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What’s different on Engineered Systems

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What’s Special on Engineered Systems?

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1.  Direct-to-wire InfiniBand protocol speeds messaging on Engineered Systems

2.   Unique Fault Tolerance allows duplicaQng IMCUs on another node (mirroring)

ODA

Engineered


Oracle Database In-‐Memory: Unique Fault Tolerance

•  Similar to storage mirroring

•  Duplicate in-memory columns on another node

-  Enabled per table/partition

-  Application transparent

•  Downtime eliminated by using duplicate after failure

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Only Available on Engineered Systems


Oracle Database In-‐Memory: Unique Fault Tolerance

•  Policy is user-‐specifiable

•  Controlled by DUPLICATE subclause

-  DUPLICATE -  DUPLICATE ALL

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ALTER TABLE sales INMEMORY DUPLICATE; ALTER TABLE COSTS INMEMORY DISTRIBUTE AUTO DUPLICATE ALL;


RAC-‐ special: Service-‐oriented Column Stores

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Services and IM Column Stores • Use services to run independent IM column stores on certain nodes

– Enables access to certain / subset of nodes – Allows to control IM column store populaQon

• Can be used to enforce applicaQon affinity

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Service IM2 Service: IM3 Service IM1 Service

IM3

IMRACDB

IMRACD1 IMRACD2 IMRACD3 IMRACD4


How to Use Services in a IM-‐RAC DB •  Services control access to database instances • RAC services should be created with srvctl (register them with the cluster) •  Example to add and start services: srvctl add service –d IMRACDB –service IM1 –preferred IMRACDB1, IMRACDB2 srvctl add service –d IMRACDB –service IM2 –preferred IMRACDB3 srvctl add service –d IMRACDB –service IM3 –preferred IMRACDB4 srvctl start service –d IMRACDB –service “IM1,IM2,IM3”

• Corresponding TNS entry example: IM1 =

(DESCRIPTION= (ADDRESS=(PROTOCOL=TCP)(HOST=MySCAN)(PORT=1521)) (CONNECT_DATA= (SERVICE_NAME=IM1)))

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How to set up Independent Column Stores

• PARALLEL_INSTANCE_GROUP – Restricts parallel query operaQons to a limited number of instances – Specify service_name or group_name (i.e. INSTANCE_GROUPS parameter)

• PARALLEL_FORCE_LOCAL – If true, then parallel server processes can only run on the local node

Oracle ConfidenQal – Internal/Restricted/Highly Restricted 38

init.ora Parameters


Running Independent Column Stores …

• Use services & parallel_instance_group to restrict access – Both, connecQons and PQ must honor service connecQon

• Can be set up to allow priority populaQon, but will restrict all PQ to the service

… on a subset of nodes

Popula9on

srvctl add service –d IMRACDB –s IMPERF –r IMRACDB1, IMRACDB2, IMRACDB3 alter system set parallel_instance_group=IMPERF scope=both sid='*';

Service IMPERF

IMRACDB



Running Independent Column Stores …

• User services & parallel_instance_group to restrict access – no overlapping of services – Both connecQons and PQ must honor service connecQon

• Must use priority of NONE and iniQate populaQon from the node (service)

… on individual nodes using mul9ple services (original example)

IMRACDB


srvctl add service –d IMRACDB –s IM2 –r IMRACDB3 alter system set parallel_instance_group=IM2 scope=both sid='IMRACDB3';

Service IM2 Service IM1 Service

IM3


Using Independent Column Stores for …

• ApplicaQon access restricted to node(s) based on service name – All "in-‐memory" applicaQon data resides in node(s) IM column store – Parallel queries are restricted to the node(s) supporQng the service

• Allows applicaQons to co-‐exist in a RAC system independently and make use of Database In-‐Memory

• parallel_force_local – can be used to insure no inter-‐node parallelism


… Applica9on Affinity


Using Independent Column Stores for …

• On Engineered Systems running with DUPLICATE or DUPLICATE ALL

• A node can be brought down and not affect response Qme SLAs

• All IMCUs in the downed node will be available in another node


… Rolling Patches and Upgrades


Join the Conversa9on

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hmps://twimer.com/TheInMemoryGuy hmps://blogs.oracle.com/in-‐memory/

Related White Papers •  Oracle Database In-‐Memory White Paper •  Oracle Database In-‐Memory AggregaQon Paper •  When to use Oracle Database In-‐Memory •  Oracle Database In-‐Memory Advisor

Related Database In-‐Memory Free Webcasts •  Oracle Database In-‐Memory meets Data Warehousing

Related Videos •  In-‐Memory YouTube Channel •  Database Industry Experts Discuss Oracle Database In-‐Memory (11:10)

•  Soxware on Silicon

Any Addi9onal Ques9ons •  Oracle Database In-‐Memory Blog •  My email: [email protected]

hmps://www.facebook.com/OracleDatabase

hmp://www.oracle.com/goto/dbim.html

AddiQonal Resources

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Oracle Database In-Memory Meets Oracle RAC