CON7437 What's New in Oracle Database 12c Release 12.1.0.2

Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |

Oracle Database 12c Release 1 (12.1.0.2)

Thomas Kyte http://asktom.oracle.com/ Oracle Server Technologies

http://asktom.oracle.com/



Oracle Database 12c Overview

Oracle Database In-Memory

Oracle Database 12c for the Developer

Oracle Database 12c for Big Data

Oracle Multitenant

Other Improvements

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Oracle Database 12c (12.1.0.1)

Oracle Multitenant

• Database consolidation

• Fast Provisioning

• Manage many as one

Oracle Automatic Data Optimization

• Smart Compression

• Automate Tiering

Data Guard Far Sync

• Zero data loss over large distances

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Oracle Database 12c (12.1.0.1)

Application Continuity

• Replay of failed transaction

Data Redaction

• Masks application data dynamically

• Transparent to application

Pattern Matching

• Sophisticated inter row pattern analysis

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Exploit memory to improve performance

Continue to improve consolidation

Simplify access to Big Data

Improve application developers experience







Oracle Multitenant

Other Improvements

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Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 7

Flip Flops

Core

ICs on board

DIMMS

SIMMs

SSD

Flash

Small Drives

Floppy

Big Drives

1993 ~$25/mb; $26,214,400/tb

2014 ~$0.007/mb; $7,645/tb


Accelerate OLTP Real Time

Analytics

No Changes to

Applications

Exploit latest

generation

hardware

CPU

Oracle Database In-Memory Goals


Until Now Must Choose One Format and Suffer Tradeoffs

Row Format Databases vs. Column Format Databases

Row

Transactions run faster on row format

– Example: Insert or query a sales order – Fast processing few rows, many columns

Column

Analytics run faster on column format

– Example : Report on sales totals by region – Fast accessing few columns, many rows

SALES

SALES

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Oracle In-Memory Columnar Technology

• Pure in-memory column format

• Not persistent, and no logging

• Quick to change data: fast OLTP

• 2x to 20x compression

• Enabled at table or partition level

• Available on all hardware platforms

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SALES

Pure In-Memory Columnar


Scans Billions of Rows per Second per CPU Core

• Each CPU core scans local in-memory columns

• Scans use fast SIMD vector instructions

• Originally designed for graphics & science

• Billions of rows/sec scan rate per CPU core

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Vec

tor

Reg

iste

r

Load multiple region values

Vector Compare all values an 1 cycle

CPU

Memory

REG

ION

CA

CA CA

CA

Example: Find all sales in region of CA

> 100x Faster







Oracle Multitenant

Other Improvements

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Oracle Database 12c Release 1 (12.1.0.2) Flexible Schema development

JSON

JSON Via RESTful service

Via Native APIs Data persisted in database

In JSON

SQL

Data analyzed via SQL

Oracle Database 12c


Querying JSON

{

"firstName": "John", “lastName”: "Smith", "age": 25, "address": { "streetAddress": "21 2nd Street", "city": "New York", "state": "NY", "postalCode": "10021“, "isBusiness" : false}, "phoneNumbers": [ { "type": "home", "number": "212 555-1234“ }, { "type": "fax", "number": "646 555-4567“ } ]

}

select

c.document.firstName,

c.document.lastName,

c.document.address.city,

c.document.phoneNumbers

from customers c;

Simplified syntax for simple queries

Sample JSON in column customers.document


Oracle REST Data Services Enabling RESTful access to Oracle Database

• Provides data access consistent with modern App Dev frameworks • Can map standard http(s) URI RESTful gets and posts to SQL • Can declaratively returns results in JSON format • JavaScript framework friendly • Can support high numbers of end users

• Services • HTTP(s) relational data access • Oracle JSON collection based schemaless access • Oracle NoSQL access over HTTP • Oracle APEX mid-tier, web toolkit applications, mod_plsql replacement

• Formally known as Oracle APEX Listener • Supported feature of the Oracle Database since 2010 • Ships with Oracle Database 12c Release 1 (12.1.0.2)


Oracle REST Data Services Schemaless development using JSON Collection API (12.1.0.2)

• Data stored in Oracle Database as JSON documents • App Developer make standard HTTP(S) calls to JSON Collection APIs

Oracle Database

URI

HTTP(S) client

Oracle REST Data Services

JSON Collection API Auto Generated SQL

Transform JSON Pass Back JSON


Oracle REST Data Services Serving JSON results from relational data

Oracle Database

URI

HTTP(S) client


Map and Bind SQL

Transform SQL Result Set Transform to JSON JSON

Data stored in standard relational tables and columns

Oracle REST Data Services (ORDS) Developer defines URI<>SQL mapping

App Developer calls named URI over HTTP(S) gets and posts


Oracle REST Data Services Serving JSON results with Oracle NoSQL Database (ORDS 3.1)

Oracle REST Data Services provides HTTP(s) access to Oracle NoSQL Oracle NoSQL is embedded within ORDS and can also access remote DB

Oracle NoSQL Database

URI

HTTP(S) client


NoSQL API Key-Value Lookup

Transform JSON Pass Back JSON







Oracle Multitenant

Other Improvements

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SQL is Critical

“….the complexity of dealing with a non-ACID data store in every part of our business logic would be too great, and there was simply no way our business could function without SQL queries.”

Google, VLDB 2013

“[Facebook] started in the Hadoop world. We are now bringing in relational to enhance that. ... [we] realized that using the wrong technology for certain kinds of problems can be difficult.”

Ken Rudin, Facebook, TDWI 2013

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http://tdwi.org/articles/2013/05/06/facebooks-relational-platform.aspx https://www.linkedin.com/groups/Find-out-why-Google-decided-4434815.S.273792742


Run the Business Scale-out and scale-up

Collect any data

SQL

Transactional and analytic

applications for the enterprise

Secure and highly available

Relational

Oracle Support for Any Data Management System

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Hadoop

Change the Business

Scale-out, low cost store

Collect any data

Map-reduce, SQL

Analytic applications

NoSQL

Scale the Business

Scale-out, low cost store

Collect key-value data

Find data by key

Web applications


Overcoming Barriers to Adoption of New Technologies

Confidential 23

INTEGRATION SKILLS SECURITY

Engineered Systems

SQL on All Data

Database Security on

All Data

SQL


Oracle Big Data SQL

Oracle Confidential – Internal/Restricted/Highly Restricted 24

One fast SQL query , on all your data.

Oracle SQL on Hadoop and beyond • With a Smart Scan service as in Exadata • With native SQL operators • With the security and certainty of Oracle Database


Accessing Big Data Without SQL Push Down

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Hadoop Cluster

All columns and rows from the table are returned

100’s of Terabytes of Data WEB_LOGS

Request for Data

Low utilization of available resources

High load on database server

Select w.sess_id, w.cust_id, w.page_id From web_logs w Where w.source_country = ‘Brazil’ And w.category = ‘TV’ And w.channel = ‘Mobile’


Big Data SQL Push Down With SQL Push Down

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Select w.sess_id, w.cust_id, w.page_id From web_logs w Where w.source_country = ‘Brazil’ And w.category = ‘TV’ And w.channel = ‘Mobile’

WEB_LOGS

SQL shipped to BDA

10’s of Gigabytes of Data

Only columns and rows needed to answer query are returned

Good utilization of available resources.

SQL executed on Hadoop cluster

Lower load on Server, Faster response

Big Data SQL Server

Hadoop Cluster



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Select w.sess_id, w.cust_id, w.page_id, c.name From web_logs w, customers c Where w.source_country = ‘Brazil’ And w.category = ‘TV’ And w.channel = ‘Mobile’ And c.customer_id = w.cust_id

WEB_LOGS

SQL shipped to BDA





Data joined between CUSTOMERS and

WEB_LOGS on server

Big Data SQL Server

Hadoop Cluster

CUSTOMERS



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Select w.sess_id, w.cust_id, w.page_id, c.name From web_logs w, customers c Where w.source_country = ‘Brazil’ And w.category = ‘TV’ And w.channel = ‘Mobile’ And c.customer_id = w.cust_id

WEB_LOGS

SQL shipped to BDA





Data joined between CUSTOMERS and

WEB_LOGS on server

Big Data SQL Server

Hadoop Cluster

CUSTOMERS

SQL Push Downs supported by Big Data SQL

• Hadoop scans (InputFormat, SerDe) • JSON parsing • WHERE clause evaluation • Column projection • Bloom filters for faster join


New Data Sources for Oracle External Tables

CREATE TABLE web_logs

(click VARCHAR2(4000))

ORGANIZATION EXTERNAL

( TYPE ORACLE_HIVE

DEFAULT DIRECTORY Dir1

ACCESS PARAMETERS

(

com.oracle.bigdata.tablename logs

com.oracle.bigdata.cluster mycluster)

)

REJECT LIMIT UNLIMITED

• New set of properties – ORACLE_HIVE and ORACLE_HDFS access drivers

– Identify a Hadoop cluster, data source, column mapping, error handling, overflow handling, logging

• New table metadata passed from Oracle DDL to Hadoop readers at query execution

• Architected for extensibility – StorageHandler capability enables future support

for other data sources

– Examples: MongoDB, HBase, Oracle NoSQL DB







Oracle Multitenant

Other Improvements

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Oracle Multitenant New architecture for consolidating databases and simplifying operations

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ERP CRM

DW Self-contained PDB for each application • Applications run unchanged • Rapid provisioning (via clones) • Portability (via pluggability)

Shared memory and background processes • More applications per server

Common operations performed at CDB level • Manage many as one (upgrade, HA, backup) • Granular control when appropriate


Multitenant New Features in 12.1.0.2 • Subset by tablespace

• Metadata-only clone

• Remote clone (including snapshots)

• File system-agnostic cloning via dNFS (clonedb = true)

• New SQL clause to aggregate data across PDBs

select ENAME from

containers(scott.EMP)

where CON_ID in (45, 49);

• New “standbys” clause

• (all | none)

• Nologging clause at PDB level

• Flashback data archive, transaction query & backout

• Temporal SQL Support

• Compatible with DB In-Memory

• Maintains state of PDBs between CDB restarts

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Cloning

SQL

Cross PDB Queries

Standby & Logging

PRIMARY STANDBY

Additional Features







Oracle Multitenant

Other Improvements

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Performance Improvements

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Advanced Index Compression

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• Compresses indexes to reduce their overall storage requirement – Less space required on disk

– Better use of the database cache

• Indexes are compressed by between 1 – 3 times

• Little or no discernable overhead

• Compression Advisor extended to describe the possible benefits of this feature


Attribute Clustering Ordering of data so that rows are stored near one another based on column values

• Improved query performance and concurrency – Reduced physical data access trough smart IO

– Significant IO reduction for highly selective operations

• Optimized space utilization – Less need for indexes

– Improved compression ratios through data clustering

• Full application transparency – Any application will benefit

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Benefits :


Zone Maps Persisted storage index

• Stores minimum and maximum of specified columns

• Analogous to a coarse index structure – Much more compact than an index

– Zone maps filter out what you don’t need, indexes find what you do need

• Significant performance benefits with complete application transparency – IO reduction for table scans with predicates on the table itself or even a joined table

using join zone maps (a.k.a. “hierarchical zone map”)

• Benefits are most significant with ordered data – Used in combination with attribute clustering or data that is naturally ordered

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X


Approximate Count Distinct

• Not every query requires a completely accurate result – “How many distinct individuals visited our website last week?”

• New SQL function for approximate results for COUNT DISTINCT aggregates – APPROX_COUNT_DISTINCT()

• Approximate results can be significantly faster and use less resources than exact calculations – 5x to 50x ++ times faster (depending upon number of distinct values and complexity

of SQL)

– Accuracy > 97% (with 95% confidence)

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1,2,3...


Rapid Home Provisioning


Oracle Rapid Home Provisioning Install Once Use Many

• Patching is complex and time consuming – Even when automated

• New way to deploy upgrades – Create reference homes on Centralized Home Server

• Apply patches once (Enterprise) on Home Server

• Distribute homes on-demand or policy

– Fast and Efficient • Rapid distribution (network efficient)

• Space efficient (snapshots)

• Local caches

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Oracle Rapid Home Provisioning

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Oracle Enterprise Manager

Database Cloud

Cluster

Cluster Cluster

Cluster

Cluster

Cluster

Differential Copy

NFS Mount

Local Gold Image

S/W Distribution

Service Catalog

Grid Home Server

Provisioning

Monitoring and Configuration

Capacity and Resource

Patching

Performance and Tuning

Service Level

Application

Database

Grid


Database Backup Logging Recovery Appliance

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B


Database Backup Logging Recovery Appliance A New Approach to Data protection in the Enterprise

Backup Windows Eliminated. No more Full Backups

Sub second transaction protection of critical data

Improved System Availability by offloading backup processing

End to end data protection by block validation throughout its lifecycle

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Architected for Protection of Critical Data

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CLOUD SCALE

• Scales to 1000s of Clients

• Petabytes of Data

• No expensive backup agents

DELTA PUSH

• DBs access and send only changed data

• Minimal impact on production servers

• Real-time redo ship for near-zero data loss

DELTA STORE

• Validated, compressed database change data

• Fast restores to any point-in-time using deltas

• Built on Exadata scaling & resilience

CLOUD SCALE

• Copy to tape: no production server load

• Tapes utilized all day

• Restore directly from tape

BB


Oracle Key Vault


Key Management Challenges Heard from Customers

Databases Servers Middleware

Management Challenges

• Proliferation of encryption wallets and keys

• Authorized sharing of keys

• Key availability, retention, and recovery

• Custody of keys and key storage files

Regulatory Challenges

• Physical separation of keys from encrypted data

• Periodic key rotations

• Monitoring and auditing of keys

• Long-term retention of keys and encrypted data


Key Management with Oracle Key Vault

• Centralized management of keys, secrets, Oracle Wallets, Java Keystores and more

• Optimized solution for Oracle Stack (Database, Middleware, Systems)

• Supports industry standard OASIS KMIP protocol

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KEY VAULT


Oracle Key Vault High-Level Architecture

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Standby

Administration Console, Alerts,

Reports

Secure Backups

Databases

Servers

Middleware

= Credential File

= Oracle Wallet

= Server Password

= Java Keystore

= Certificate

KEY VAULT


Oracle Advanced Security Transparent Data Encryption (TDE) Oracle Wallet Scenarios

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Single Instance

KEY VAULT

GoldenGate

Multiple DBs Same Machine

RAC

Data Guard


Oracle Advanced Security Transparent Data Encryption (TDE) Direct Connection Scenarios

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Single Instance

KEY VAULT

Multiple DBs Same Machine

RAC

Data Guard

GoldenGate


Oracle Key Vault Software Appliance Platform

• Turnkey solution based on hardened stack

• Includes Oracle Database and security options

• Open x86-64 hardware to choose from

• Easy to install, configure, deploy, and patch

• Separation of duties for administrative users

• Full auditing, preconfigured reports, and alerts

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Session ID: CON7486 Session Title: Developers Rule the World (Again) Venue / Room: Moscone South - 303 Date and Time: 9/29/14, 16:00 - 16:45 Session ID: CON9027 Session Title: YesSQL! A Celebration of SQL and PL/SQL Venue / Room: Moscone South - 103 Date and Time: 9/29/14, 18:30 - 20:00 Session ID: CON7439 Session Title: SQL Is the Best Development Language for Big Data Venue / Room: Moscone South - 104 Date and Time: 9/30/14, 10:45 - 11:30

Session ID: CON7501 Session Title: Five More Things About SQL and PL/SQL Venue / Room: Moscone South - 303 Date and Time: 9/30/14, 15:45 - 16:30 Session ID: CON8450 Session Title: SQL (and PL/SQL) Tuning Experts Panel Venue / Room: Moscone South - 306 Date and Time: 9/30/14, 17:00 - 17:45 Session ID: CON7485 Session Title: Securing Data in Oracle Database 12c Venue / Room: Moscone North - 131 Date and Time: 10/1/14, 11:30 - 12:15

Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 53

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CON7437 What's New in Oracle Database 12c Release 12.1.0.2