商品簡介
Save time and money with DB2 10 for LUW--Even travel through time and shrink data!
How would you like to compress even more data, store it in a cloud, and analyze it as though you are traveling through time without compromising security' In addition to these enhancements, you will experience lower costs and faster performance with the latest release of DB2. Read this book to understand the power of DB2 10 and get started now!
This book provides you with the comprehensive knowledge you need to get started with the latest DB2 release. Try the some of the new features by downloading DB2 Express for free, which features Big Data and Cloud technology. Go to ibm.com/db2/express.
Table of contents
Front Matter 5 pages
Dedication, bios, exec. letter, and about this book (tour)
Chapter 1 ' An Overview of DB2 V10 5 pages
' Save Time and Money
o Adaptive data compression provides up to XX% improvement over IBM's existing compression
o Multi-temp storage allows you to optimize data storage and cost efficiency
o Time travel query improves developer and DBA productivity
o Lower cost than Oracle with 98%+ PL/SQL compatibility making it easy to migrate to DB2
' Reliable Top Performance
o Deep exploitation of H/W to maximize efficiency
o 3x more efficient performance per core than Oracle for TPC
o DB2 pureScale offers superior scale-out efficiency and easier scale-out vs Oracle RAC
Part I ' Same Time and Money 70 pages
Chapter 2 ' DB2 for Storage Optimization 15 pages
' Adaptive compression
' Reduced user management of compression
' Avoid data outage to recompress data
' Obtain higher/consistent compression rates through data changes (new/updated data)
' Reduce the cost of storage and memory for the warehouse implementation and optimize our ability to exploit SSD. Will provide 30% over existing compression and even greater on SAP Data.
' Hit home we are total database compression so recap past ' many vendors talk about table compression
' Log compression
' Reclaim of unused storage via automatic shrink/reduce
Chapter 2 ' DB2 for Temperature Controlled Storage 10 pages
' What is it
' How it works
' Workload Management integration
' Example of usage and time savings
' Flexibly optimize storage to suite individual needs
' Maximize the amount of data managed within a warehouse or OLTP deployment while being able to also meet business service levels on performance and data history
Chapter 3 ' DB2 for Time Travel Query 15 pages
' Why time travel query
' Contrast with the old programmatic way and time savings: up to XX% less code needed (show examples of old way and new way)
' Capabilities of time travel query
' Forward (unique) and backwards,
' +++
' Business examples
Chapter 4 ' DB2 for Easy Migration 5 pages
' Recap of `the story'
' Latest conversion 98%+ - reference to Gartner and other quotes about it
' What's new as we round it out
' Mention of Forms
' How it works
Chapter 5 ' DB2 for a Secure Operating Environment 15 pages
' Recap of LBAC and other security enhancements (SoD, PLP) over the releases and benefits of LBAC over LBS
' FGAC: Access Control Definitions
' Providing the ability to consolidate more users and applications onto a single database without the impact security constraints causing duplication of data or complex application driven security causing performance headaches through complex predicates.
' Application development: Application logic is NOT sensitive to the roles and their views
Chapter 6 ' DB2 for Easy Management 10 pages this could be removed I think .. we will see
Y Storage Groups
Y New tools from Optim and Data Studio
Y '''''
Part II ' Reliable Top Performance 35 pages
Chapter 7 ' DB2 for Performance 20 pages
' DB2 pureScale enhancements for performance
' Query Performance and stability
' Multi-core parallelism
' Provide vertical and horizontal growth strategy
' Maximum performance and scaling for new many-core processors. DB2 enhancements to improve performance of both transactional and warehousing workloads on servers that have a large number of cores and memory on a single server
' Improved pureXML performance
' Support for Binary XML and new XML index types improves the response times of applications using pureXML
' Performance Stability
' Cardinality Estimation
' Auto RUNSTATS on statviews
' Improved matching (partial statview matching)
' Expressions on statviews
' Statsview advisor ' schema/workload based
' Non-join statsviews
' Costing Enhancements
' Improve performance stability in query execution
' Improvements in FETCH I/O, Bufferpool hit ratio, QRW and SORT costing
' Optimizer Guidelines
' Support wildcarding in the use of guidelines
' Continual data ingest
' Deliver more timely business decision making for organizations that have large data volumes that need to be analyzed in near real time to prevent fraud, customer churn and increase potential
' The Not So Little things that make DB2 go faster
' Compile time performance
' Handle larger join queries
' Overall compile time improvements
' Join expressions
' Handling more than just simple C1 = C2 expressions with Merge Joins and Hash Joins
' Improved Index Access
' Index Skip-Scan
' RUNSTATS Performance
' Index page sampling
' Distribution stats performance improvement
' Range Partition Table Enhancement
' Improvements to roll-in data via Attach
' Removal of z-lock during Attach processing
' Increased concurrency
' Workload Management
' Ensure a consistent level of performance from your DB2 database by providing a finer control over the amount of resources used by workloads across all platforms. Eliminates the need to configure and maintain operating system WLM schemes. Enable Adaptive Profiles for servicing Shift based Service level
' Zigzag join
' Runstats
' Partial Early Distinct and Aggregation
' Sampling for stats gathering on indexes
' Jumpscan
' Index scan enhancements
' Prefetching enhancements
' Star Join Improvements ' Zig Zag joins
' Using ZIG ZAG joins, DB2 identifies and optimizes Star Schema queries by 5x.
' Optimized star joins
' Early Distinct
' Remove duplicates and reduce data early
' Later operations process less data (smaller joins, less data communication in DPF less spilling etc.,)
' Aggregate Performance
' Aggressive eager aggregation (partial) pushed down below other operations (joins)
' Use hash aggregation to avoid spilling of large SORTs
' Improve Performance of basic aggregation function code path
' Sort Performance
' Improve choice and performance of existing SORT algorithms
' Hash Join Performance
' Improve one of the most common join methods used in a Data warehouse system
Chapter 8 - DB2 for Availability 15 pages
' DB2 pureScale enhancements for availability
' Multiple HADR standbys
' Q-Replication enhancements
' Requirements.
' DB2 managed dispatch intervals
' Dynamic Registry Variables
' Reduce the need to recycle DB2 for variables to take effect
' Integrated HA enhancements
' Active/Active: HADR for the Warehouse
' Enables customers to have continuous warehouse availability and workload balancing across co-located or geographically dispersed systems. Providing greater availability and performance. Based on Q-Rep technology
' Read only workloads
' UR isolation level
' Application Balancing
' Write detection and redirection
' Monitoring and Workload Management
' Backup
' Data Sub-setting
' Disaster Recovery and Active/Active Warehousing
' Extend SQL with JAQL
' Availability Odds and Ends
' Enable Concurrent Volume Group support with TSA
' Reduced outage due to elimination of disk acquisition during failover
' Implement Distributed failover policy
' N -> N-1 model
' Partitions on failed host get distributed amongst other surviving hosts
' Increased throughput & Reduced resource utilization compared to cluster pairs
' Reduce Impact of Catalog Partition Failure
' Allow existing applications to continue executing
' Resilience Enhancements
' Toleration of errors during Write
Part III ' Support of Next Generation Applications 15 pages
Chapter 9 - DB2 for All Kinds of Data 10 pages
o Map/Reduce Overview
' Hadoop Overview
' Extend SQL with JAQL
o XML Enhancements
o RDF Graph
' Support for Next Generation Applications
o Support for NoSQL data formats lime native XML and graph RDF triples
o Continuous data ingest for real-time operational analytics and OLTP
o Support for public and private cloud environments
o Connectors for Big Data environments (Hadoop, Streams, Netezza, +++)
' Continuous Data Ingest, Temporal, multi-tier storage, Adaptive compression, pureScale, FGAC, HA (Q-based HA and DR and multi-standby), Oracle compatibility updated, query performance
Chapter 10 ' DB2 on the Cloud 5 pages
