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C2090-614 - DB2 10.1 Advanced DBA for Linux UNIX and Windows - Dump Information

Vendor : IBM
Exam Code : C2090-614
Exam Name : DB2 10.1 Advanced DBA for Linux UNIX and Windows
Questions and Answers : 108 Q & A
Updated On : April 19, 2019
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C2090-614 Questions and Answers

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C2090-614 DB2 10.1 Advanced DBA for Linux UNIX and Windows

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C2090-614 exam Dumps Source : DB2 10.1 Advanced DBA for Linux UNIX and Windows

Test Code : C2090-614
Test Name : DB2 10.1 Advanced DBA for Linux UNIX and Windows
Vendor Name : IBM
Q&A : 108 Real Questions

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IBM DB2 10.1 Advanced DBA

DB2 join (eventually) gets IBM i 7.1 assist | killexams.com Real Questions and Pass4sure dumps

IBM this month announced a brand new unencumber of DB2 connect, a piece of middleware used to connect customer applications running on Linux, Unix, or windows platforms to DB2 database servers operating on IBM i and z/OS. With DB2 join edition 10.1, IBM delivered assist for DB2 for i edition 7.1. It additionally delivered a couple of aspects for taking advantages of the newest enhancements to DB2 for z/OS.

DB2 join makes it possible for customer functions to create, access, replace, handle, and manipulate DB2 databases on host systems the usage of quite a lot of languages, including SQL, ODBC, JDBC, DB2 APIs, SQLJ DB2 call degree Interface (CLI), .web, Hypertext Preprocessor, Ruby, Python, Perl, and pureQuery. essentially the most average use of the software is serving SQL statements to DB2 on IBM i and z/OS techniques, however can also be used to be a part of tables from diverse DB2/400 databases, together with different DB2 types and Informix, and even Oracle, SQL Server, and Sybase when coupled with that most efficient large Blue information broking service, WebSphere guidance Integrator.

The lone IBM i-connected enhancement in DB2 join 10.1 is a biggie: support for DB2 for i operating on the latest IBM i edition 7.1 operating device, which shipped two years ago this month. Late support is superior than no guide.

the bulk of the enhancements in DB2 connect 10.1 focus on the various drivers to support the latest capabilities in DB2 10 for z/OS platform, which IBM shipped in October 2010. This comprises: binary XML guide in Java drivers; XML-connected efficiency boosts; assist for prolonged vector variables; temporal desk aid; superior timestamp precision; and different performance and high availability enhancements.

This free up also can provide stronger aid for IBM equipment, together with WebSphere application Server, Optim Configuration manager, and facts Studio. Programmers may be chuffed to hear DB2 join 10.1 brings: new JDBC four.1 capabilities for Java 7; guide for the .web 4.0 framework with Entity Framework; full integration with visual Studio 2010; and guide for migrating applications from different database carriers to DB2 for z/OS.

IBM has also transformed its a variety of DB2 connect bundles, together with shrinking the footprint of its facts Server (DS) Driver bundle; streamlined activation of DB2 join limitless version for equipment z; and new gateway options.

groups operating the superior IBM pureQuery Runtime for Linux, Unix, and windows will see new safety aspects, together with the skill to keep away from SQL injection by way of restricting the SQL accomplished with the aid of a selected utility to selected SQL statements. This unlock additionally gives users the means to convert dynamic SQL to static SQL, which improves efficiency and security.

DB2 join 10.1 editions turn into obtainable June eleven. For extra suggestions on DB2 join 10.1, see IBM u.s. software Announcement 212-076.

linked studies

Raz-Lee Claims IBM i facts-access step forward with DB-Gate

DB2 connect gets greater aid for saved methods and Triggers

IBM officially broadcasts i/OS 7.1

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IBM's DB2 database update does time go back and forth, receives graphic | killexams.com Real Questions and Pass4sure dumps

With the launch of DB2 10.1, large Blue is adding a slew of new facets that make DB2 greater advantageous for modern, massive-records workloads.

counting on how you want to count it, IBM is both the area's quantity-two or quantity-three seller of database management methods, and it has loads of secondary methods and functions business that are pushed off its DB2 databases.

be aware that we mentioned DB2 databases. IBM has three different DB2s, not only 1. there's DB2 for the mainframe, DB2 for its midrange IBM i (formerly OS/400) platform, and DB2 for Linux, Unix, and home windows platforms.

it's the latter one, standard on occasion as DB2 LUW, that became revved as much as the ten.1 unencumber level on Tuesday. Concurrent with the database improve, IBM is additionally upgrading its InfoSphere Warehouse – a superset of DB2 designed for statistics warehousing and OLAP serving – to the 10.1 degree.

At a really excessive degree, explains Bernie Spang, director of product method for database software and methods at IBM, the DB2 10.1 free up is focused on two issues: the problem of coping with big records, and automating greater of "the drudgery of the mechanics of the statistics layer" in applications.

The update to DB2 and InfoSphere Warehouse, which both ship on April 30, is the culmination of 4 years of construction by using hundreds of engineers working worldwide from IBM's software labs. the new database additionally has a number of efficiency enhancements, a new statistics-compression formula, and expanded compatibility with Oracle databases to aid inspire Oracle shops to make the bounce.

On the huge-information front, IBM has juiced the connector that links DB2 to Hadoop MapReduce clusters running the Hadoop distributed File system (HDFS). Spang says that the prior Hadoop connector changed into "rudimentary", and so coders went back to the drafting board and created an improved one which makes it possible for for statistics warehouses to more without difficulty suck in facts from and spit out information to Hadoop clusters, with less work on the part of database admins.

IBM DB2 10 versus InfoSphere Warehouse 10

IBM's DB2 10 versus InfoSphere Warehouse 10 (click to magnify)

the brand new DB2 also helps the storing of graph triples, that are used to do relationship analytics, or what's every so often called graph analytics.

rather than searching through a mountain of information for certain subsets of advice, as you do in a relational database or a Hadoop cluster, graph analytics walks you through the entire possible combos of statistics to look how they're related. The links between the facts are what's vital, and these are constantly shown graphically the usage of wire diagrams or other strategies – therefore the name graph analysis.

Graph data is kept in a different layout called aid Definition Framework (RDF), and also you query an information shop with this facts the usage of a question language called SPARQL.

The Apache Jena project is a Java framework for building semantic web applications in response to graph information, and Apache Fuseki is the SPARQL server that techniques the SPARQL queries and spits out the relationships so that they will also be visualized in some style. (Cray's new Urika system, announced in March, runs this Apache graph analysis stack on right of a massively multithreaded server.)

identical to they imported objects and XML into the DB2 database in order that they could be listed and processed natively, IBM is now bringing within the RDF format so that graph triples may also be kept natively.

As IBM explains it – not strictly grammatically, to a few English majors – a triple has a noun, a verb, and a predicate, reminiscent of Tim (noun) has received (verb) the MegaMillions lottery (predicate). you can then query all aspects of a set of triples to look who else has won MegaMillions – a short listing, in this case.

In checks among DB2 10.1 early adopters, functions that used these graph triples ran about 3.5 instances faster on DB2 than on the Jena TDB facts keep (short for triple database, most likely) with SPARQL 1.0 hitting it for queries.

DB2 10.1 for Linux, Unix, and home windows platforms additionally includes temporal good judgment and analysis services that enable it to do "time commute queries" – features that IBM brought to the mainframe variant of DB2 final 12 months. by way of now helping native temporal records codecs interior the database, that you can do AS OF queries in the past, latest, and future throughout datasets while not having to bolt this onto the aspect of the database.

"This dramatically reduces the volume of application code to do bi-temporal queries," says Spang, and you can do it with SQL syntax, too. you could flip time shuttle question on or off for any table inner the DB2 database to do old or predictive evaluation throughout the facts units. RDF file layout and SPARQL querying can be found across all editions of DB2 10.1.

Like different database makers, IBM is fixated on facts compression techniques no longer simplest to cut back the quantity of actual storage shoppers should put under their databases, however additionally to pace up performance. With DB2 9.1, IBM brought desk compression, and with the more contemporary DB2 9.7 from just a few years returned, brief house and indexes were compressed.

With DB2 10.1, IBM is adding what it calls "adaptive compression", which capability applying data row, index, and temp compression on the fly as best suits the wants of the workload in query.

In early checks, consumers noticed as a great deal as an 85 to ninety per cent reduction in disk-means necessities. Adaptive compression is constructed into DB2 superior business Server edition and commercial enterprise Developer edition, however is an add-on for an additional fee for enterprise Server version.

efficiency boosts, administration automation

On the performance front, IBM's database hackers have tweaked the kernel of the database to make enhanced use of the parallelism in the multicore, multithreaded processors that are ordinary nowadays, with particular performance enhancements for hash joins and queries over superstar schemas, queries with joins and sorts, and queries with aggregation.

Out of the box, IBM says that DB2 10.1 will run as much as 35 per cent quicker than DB2 9.7 on the equal iron. With the entire information compression grew to become on, many early shoppers are seeing an element of three enhanced efficiency from their databases. Which means – sorry, techniques and technology group – many DB2 purchasers are going to be capable of get improved performance while not having to buy new iron.

On the management front, DB2 now has integrated workload administration aspects that can cap the percentage of total CPU capacity that DB2 is allowed to devour, with tough limits and gentle limits across diverse CPUs which are sharing means. that you can also prioritize critical DB2 workloads with diverse classes of carrier stage agreements.

Database indexes now have new features reminiscent of start scan, which optimizes buffer usage in the underlying device and cuts down on the CPU cycles that DB2 eats, in addition to sensible prefetching of index and records to boost the performance of the database, an awful lot as L1 caches in chips do for his or her processors.

DB2 now additionally has a multi-temperature facts administration characteristic that is aware of the difference between flash-primarily based SSDs, SAS RAID, SATA RAID, and tape or disk archive, and can automagically stream database tables which are scorching, warm, cold, and downright icy to the appropriate equipment.

entry control is a large deal, and DB2 10.1 now sports fine-grained row and column access controls so each and every user coming right into a system can also be locked out of any row or column of facts. Now, personnel handiest see the records they deserve to be aware of, and you won't have to partition an software into diverse courses of clients. You simply do it on the consumer level based on database guidelines. This function masks simply the information you don't seem to be speculated to see.

IBM continues to ramp up its compatibility with Oracle's PL/SQL question language for its eponymous databases, and says that with the 10.1 liberate, early entry clients are seeing an ordinary of ninety eight per cent compatibility for Oracle PL/SQL queries working against DB2. it's now not 100 per cent, nevertheless it is getting nearer.

finally, as far as huge aspects go, the other new one is referred to as "continuous records ingest", which makes it possible for for external facts feeds to continuously pump statistics into the database, or for the database to always pump into the statistics warehouse, without interrupting queries operating on both field. This ingesting relies on bringing the information into the database and warehouse in a parallel trend, with varied connections, but precisely how it works is not clear to El Reg as we go to press. It seems a bit of like magic.

DB2 specific-C is free and has the time commute function; it is capped at two processor cores and 4GB of leading memory. DB2 specific adds the row and column entry manage, label entry control (an present characteristic) excessive availability clustering features (new with this unencumber), and has a reminiscence cap of 8GB and might run throughout 4 processor cores; it charges $6,490 per core.

Workgroup Server boosts the cores to 16 and the memory to 64GB, and would not have the HA aspects. enterprise Server has the multi-temperature information administration function and costs $30,660 per core. The properly-end advanced business Server has the entire bells and whistles, including optimizations and equipment to make DB2 play better in an information warehouse. Pricing for the Workgroup Server and advanced business Server had been not available at press time. ®

subsidized: becoming a practical security chief


IBM Db2 Statistical features for Analytics | killexams.com Real Questions and Pass4sure dumps

unless these days, business analytics towards large records and the enterprise records warehouse needed to come from subtle utility applications. This become as a result of many statistical features reminiscent of medians and quartiles were now not obtainable in fundamental SQL, forcing the applications to retrieve significant outcome sets and function aggregations and information in the neighborhood. nowadays, many database administration techniques have included these functions into SQL. This includes IBM's flagship product, Db2.

fundamental Analytics

Many giant IT retail outlets implemented huge statistics solutions over a decade in the past. at that time, the science of information changed into well-established. company analysts already had loads of event examining subsets of information from operational techniques as well as time collection data in the business records warehouse. These analyses blanketed basic statistical features equivalent to minima, maxima and skill, as well as advanced features akin to percentiles, cubes and rollups.

together with big records options got here application programs that allowed enterprise analysts to use a visible interface to choose statistics aspects and specify aggregation standards and statistical calculations. The utility then immediately creates SQL to accumulate the valuable information. despite the fact, a critical efficiency situation arose with huge information. whereas scanning gigantic amounts of information straight away changed into a characteristic of massive statistics solutions, superior statistical calculations could not be finished there.

This required returning massive amounts of records to the analyst’s application, which required a configuration with enormous quantities of memory and CPU vigor. This additionally spawned the conception of developing local facts marts to cling subsets of the warehouse and big statistics as a way to run extensive statistical calculations in the community. luckily, database administration methods (DBMSs) stepped up and delivered numerous new SQL functions to assist enterprise analysts.

Most DBMSs already offered simple statistical operations such because the following:

  • Sum, minimal and highest
  • standard (arithmetic mean)
  • ordinary deviation
  • Variance and covariance
  • Correlation
  • In up to date DBMSs that support a big information answer (and, to a lesser extent an enterprise records warehouse), it's now indispensable to guide greater superior capabilities for usability and efficiency explanations.

    IBM Db2 SQL Enhancements

    IBM has implemented numerous statistical functions in its flagship relational database product Db2. These encompass Median and Percentiles in addition to dice and Rollup.

    Median

    Calculating a regular of a group of numbers appears like a simple operation. despite the fact, the term “regular” has multiple meanings in data. Three of those are the imply, the median and the mode. Even the imply has a number of diversifications. The arithmetic suggest is essentially the most familiar mean, and this characteristic has existed in ANSI regular SQL for decades. In fresh version of Db2, IBM has extended its SQL variant to encompass a median function.

    Percentiles

    The percentile is an aggregate function that returns the records price inside a group of values that corresponds to a given percentile. For clarity, the median cost of a group of numbers is the cost it is at the fiftieth percentile. If the variety of values within the group is even, then the median is interpolated as being between both nearest values. for instance, in the set (1, 2, three), the quantity 2 is the median, or fiftieth percentile. within the set (1,2,3,4) the median is calculated as 2.5. Percentiles are a typical way of depicting facts graphically, the most standard example being pie charts.

    The percentile function continues information aggregation, sorting and calculation operations on the host laptop, keeping off downloads of massive outcomes sets for native calculation. It additionally simplifies SQL statements, enabling the database administrator (DBA) the opportunity to capture and tune analytical queries with the intention of expanding performance and lowering resource usage. as an instance, if medians and percentiles are required for a specific column price, the DBA could agree with an index on that column; then again, there are numerous strategies (mentioned beneath) to “pre-aggregate” average calculations.

    dice and Rollup

    The cube and rollup services are identical, in that they are a way for analyzing subtotals of a bunch of data items, with rollup being a subset of dice. for example, consider an enterprise accounting device with assorted bills owned via each branch. to analyze account balances across the organization an analyst wishes to calculate subtotals for each and every department, in addition to an standard complete. in this state of affairs, the debts roll up to departments, which then roll as much as a grand total. This should be would becould very well be coded in SQL in this means:

    opt for  Department_ID, SUM (Account_Balance)

    FROM  Account_Table

    community by means of ROLLUP (Department_ID)

    ORDER by  Department_ID

    This SQL remark generates a influence set with an account balance subtotal row for each department adopted by means of a ultimate grand complete row. extra advanced statements are viable, together with assorted tiers of subtotals and specification of different grouping features. As with medians and percentiles, including the rollup definition within the SQL makes it possible for the DBMS to do a single flow of the statistics and perform the necessary calculations correctly.

    The cube function works in an identical fashion through permitting specification of grouping standards. (See hyperlink on the end of this article for details.)  accept as true with the following Account desk:

    Account_Table

    Account_IDBalanceCustomer_IDCustomer_TypeAccount_TypeCustomer_Region...

    The closing three columns are candidates for grouping, as a business analyst may also wish to overview a summary of money owed for selected customer forms or account types, or they could are looking to evaluate consumers across numerous regions. in terms of the rollup function, the need might be to create subtotals for each of these columns, or for combinations of these columns. Some feasible necessities could be:

  • ordinary steadiness for every consumer type
  • minimal and maximum stability for each combination of consumer class and account category
  • common balance in every area with subtotals for each customer category
  • rather than code numerous SQL statements for each possible rollup, the dice feature may also be used to accomplish this in a single remark:

    opt for  Customer_Type, Account_Type, Customer_Region, SUM(Account_Balance)

    FROM Account_Table

    neighborhood with the aid of dice  (Customer_Type, Account_Type, Customer_Region)

    ORDER with the aid of  (Customer_Type, Account_Type, Customer_Region)

    The effect back by means of this statement is a effect set of rows with the following:

  • Subtotal for every mixture of (Customer_Type, Account_Type, Customer_Region)
  • Subtotal for each mixture of (Customer_Type, Account_Type)
  • Subtotal for each and every aggregate of (Customer_Type, Customer_Region)
  • Subtotal for each and every mixture of (Account_Type, Customer_Region)
  • Subtotal for each and every combination of (Customer_Type)
  • Subtotal for every combination of (Account_Type)
  • Subtotal for each aggregate of (Customer_Region)
  • Grand total
  • The means of this enormously primary SQL observation to carry distinctive rollups is a fine boon to each the business analyst and the DBA. Simplified SQL capability fewer error, easier debugging and greater awareness of tuning wants.

    Tuning for Analytics

    The DBA who supports enterprise analysts has several options for cutting back device resources whereas supplying quick question response times. One system is to put in force a large records answer such because the IBM Db2 Analytics Accelerator (IDAA), a hybrid of software and hardware that combines a major disk storage array with hugely parallel processing. Allocating Db2 tables in the IDAA permits the Db2 Optimizer to direct SQL statements towards these tables to the IDAA, and this continually potential extremely quick query execution instances. an additional choice is to keep tables in each native Db2 and in the IDAA. The potential of this option is to deliver assorted entry paths to a particular table, when you consider that native Db2 tables can have indexes described on their columns.

    a third alternative is to create summary tables, occasionally called materialized query tables (MQTs). The DBA creates these tables via defining an SQL commentary it truly is used to populate the table, after which defining the instances when the SQL observation is to be accomplished. An instance will assist clarify this.

    consider our Account desk described previous:

    Account_Table

     

    Account_ID

    steadiness

    Customer_ID

    Customer_Type

    Account_Type

    Customer_Region

    ...

    expect that Account_Table exists in a knowledge warehouse. This capability that it isn't a part of an operational gadget with ongoing on-line exercise and batch procedures; rather, it contains rows that are loaded once per day and stay static all over the day. Let’s also assume that the DBA has captured and analyzed common SQL statements submitted with the aid of business analysts and decided that many queries require subtotals by using Customer_Region.  it's, many queries comprise here SQL syntax:

    select  SUM (Account_Balance), ...

    FROM  Account_Table

    community with the aid of ROLLUP (Department_ID)

    ...

    For this static table, the rollup is calculated each time one of those queries executes, with identical consequences. The DBA can lessen aid usage by using making a materialized question table like this one:

     

    CREATE table  Rollup_Acct_Dept_ID

       AS (select  SUM (Account_Balance), ...

         FROM  Account_Table

               community with the aid of ROLLUP (Department_ID)

               ...

    After developing this desk, the DBA concerns the REFRESH command to populate it. desk Rollup_Act_Dept_ID now carries rows with the subtotal counsel from Account_Table. because the desk records is static in this example, the rollup data want simplest be calculated once per day. Queries that need the rollup statistics can now question the MQT without delay; on the other hand, they could continue to be coded as-is, and the Db2 Optimizer will automatically entry the MQT instead of re-calculate the subtotals.

    summary

    in the early days of big information, business analysts grew accustomed to getting fast consequences from their queries. youngsters, tables grew, both in variety of columns and in the variety of current rows, and queries grew to become more complex and required lager amounts of statistics. eventually, SQL analytical query performance grew to be an issue.

    one of the crucial difficult performance concerns was the enhance in complexity of the statistical techniques and methods performed on the records. statistics-intensive services that required distinct aggregations and subtotals or different features that have been now not supported directly in SQL needed to be carried out via the analyst’s software. This led to gathering gigantic result units and transporting them from the massive facts application across the network to enable the BI utility kit to comprehensive the calculations.

    IBM’s Db2 now includes SQL alternatives that can perform such distinct statistical features equivalent to percentiles and cubes within the DBMS. This no longer best vastly reduces the volume of information traversing the community, it also gives the DBA opportunities to tune whole sets of tables and applications instead of one SQL remark at a time.

     # # #

     For more tips:

    See all articles with the aid of Lockwood Lyon


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    DB2 10.1 Advanced DBA for Linux UNIX and Windows

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    DB2 9 for Linux, UNIX, and Windows: DBA Guide, Reference, and Exam Prep (6th Edition) - Page 6 | killexams.com real questions and Pass4sure dumps

    DB2 Extenders

    DB2 Extenders offer the ability to manipulate data outside of conventional rows and columns to include the manipulation of special data types (for example, spatial types that have associated LAT/LONG coordinates and SQL-based functions to operate on them), searching services, and more. The purpose of the DB2 Extenders is to provide for the management of this data through the familiar DB2 SQL API.

    The DB2 Extenders encapsulate the attributes, structure, and behavior of these unstructured data types and stores this information in DB2. From the developer's perspective, the DB2 Extenders appear as seamless extensions to the database and enable the development of multimedia-based applications. In other words, a spatial data type is no different than a built-in data type that they may be accustomed to. This section briefly details the DB2 Extenders that are provided by IBM.

    DB2 Spatial Extender

    The DB2 Spatial Extender (DB2 SE) provides the ability to create spatially aware data objects and store them within your DB2 database, along with other spatially related objects like (LAT/LONG) coordinates and more. Almost all industries could benefit from this free technology in DB2. For example, the banking and finance industry could visually envelope customer segments for brand location identification. Municipal governments could use this technology for flood plain identification, the retail industry for billboard locations, and more. This seems apparent when you consider that almost all data has some sort of spatial component to it: we all have an address, merchandise in a warehouse has a stock location, and so on.

    The business benefit of the DB2 SE lies in the notion that it's a lot easier to spot visually represented information than data reported in rows and columns.

    When you enable your DB2 database for the DB2 SE, you can interact with your data using SQL or specialized spatial tools from other vendors. The point is that with the DB2 SE, DB2 understands the spatial "dialect" and the operations that you want to perform with it.

    For example, a telematics application on a PDA may provide its users with a list of nearby Chinese restaurants that serve Peking Duck based on the dynamic request of this user. In this case, after the client's PDA creates a location box using Global Positioning System (GPS) coordinates, it could generate SQL statements similar to the following:

    SELECT NAME, DESCRIPTION, ADDRESS from RESTAURANTS WHERE OVERLAPS (location, box(getGPS(),2000,2000)) AND category = 'chinese' AND doc Contains(menu,'Peking duck');

    OVERLAPS is a spatial function that shows interested data in a binding box defined by the OVERLAPS boundary specification; there are many other spatial functions, including INTERSECTS, WITHIN, BUFFERS, and so on.

    DB2 Geodetic Extender

    The DB2 Geodetic Extender builds upon capabilities available in the DB2 Spatial Extender and adds compensation for real-world objects like the curvature of the earth's surface. The algorithms in this extender seek to remove the inaccuracies introduced by projections and so on. This extender is available only for DB2 Enterprise as part of the Data Geodetic Management feature.

    DB2 Net Search Extender

    The DB2 Net Search Extender (DB2 NSE) combines in-memory database technology with text search semantics for high-speed text search in DB2 databases. Searching with it can be particularly advantageous in Internet applications where performance is an important factor. The DB2 NSE can add the power of fast full-text retrieval to your DB2 applications. Its features let you store unstructured text documents of up to 2 GB in databases. It offers application developers a fast, versatile, and intelligent method of searching through such documents.

    Additionally, the DB2 NSE provides a rich set of XML searching capabilities with advanced search features like sounds-like, stemming, and so on. It is shipped free in DB2 9 (it was a chargeable extender in DB2 8) to facilitate non-XML index searching of XML data stored in pureXML columns.

    DB2 XML Extender

    The DB2 XML Extender is provided with DB2 and allows you to store XML documents in DB2; it also gives you the ability to shred and store XML in its component parts as columns in multiple tables. In either case, indexes can be defined over the elements or attributes of an XML document for fast retrieval. Furthermore, text and fragment search can be enabled on the XML column or its decomposed parts via the DB2 Net Search Extender. The DB2 XML Extender can also help you formulate an XML document from existing DB2 tables for data interchange in business-to-business environments.

    You may recall that the pureXML add-on feature pack is available for all DB2 9 data servers. Indeed, this can cause confusion since the DB2 XML Extender is shipped for free in DB2 9. You should consider the DB2 XML Extender as stabilized technology. In other words, it is no longer being enhanced and shouldn't be considered for most XML applications. The DB2 XML Extender's approach to storing XML is to shred the XML to relational tables or stuff it into a large object. When you use this technology to persist XML data, you have to make serious trade-offs with respect to performance, flexibility, and so on. In addition, you have to use specialized functions to implement Spathe searches, and data types are abstracted from base DB2 data types. Quite simply, the way you interact with the DB2 XML Extender isn't natural for XML programmers and DBAs alike.

    In contrast, the pureXML feature in DB2 9 provides services such that no compromises between flexibility (what XML was designed for) and performance (one of the reasons why you want the data server to store your XML) need to be made when storing your XML data. For example, to generate XML documents from relational tables, you simple use the SQL/XML API instead of the cumbersome DB2 XML Extender functions. You can validate XML documents against Sods instead of only document type definitions (Ds) as is the case with the DB2 XML Extender, and more. We strongly recommend this feature for most of your XML-based applications.

    DB2 Administration

    DB2 DBAs have a number of graphical-based tools they can use to manage and administer DB2 data servers. Alternatively, a DBA can also use a script-based approach to administer the data environment using the DB2 tools to create and schedule the scripts. This section briefly details the main graphical tools available with DB2.

    Control Center

    The Control Center is the central point of administration for DB2. The Control Center provides DBAs with the tools necessary to perform typical database administration tasks. It allows easy access to other server administration tools, gives a clear overview of the entire system, enables remote database management, and provides step-by-step assistance for complex tasks.

    Figure 1–17The DB2 Control Center

    The All Systems object represents both local and remote data servers. To display all the DB2 systems that your system knows about, expand the object tree by clicking on the plus sign (+) next to All Systems. In Figure 1–17, you can see a DB2 data server called PAULZ contains a DB2 instance called DB2, in which the database TEST is located.

    When you highlight an object, details about that object are shown in the Contents Pane.

    The main components of the Control Center are:

  • Menu Bar — Used to access Control Center functions and online help.

  • Tool Bar — Used to access other DB2 administration tools, such as the Command Editor, Task Center, and more.

  • Objects Pane — This is shown on the left side of the Control Center window. It contains all the objects that can be managed from the Control Center as well as their relationship to each other.

  • Contents Pane — This is found on the right side of the Control Center window and contains the objects that belong or correspond to the object selected in the Objects Pane.

  • Contents Pane Toolbar — These icons are used to tailor the view of the objects and information in the Contents pane. These functions can also be selected in the View menu.

  • Task Window — Lists the most common tasks associated with the selected object in the Object Pane. In Figure 1–17 you can see that since a database is highlighted, common tasks and administrative functions related to it are in this window.

  • Hover Help — Provides a short description for each icon on the toolbar as you move the mouse pointer over the icon.

  • The Control Center also comes with personality control that you can use to adjust the view and functions available from the Control Center's tree view of your data server. For example, you can limit the Object Pain view to show just Tables or Views, as well as limit the actions you can perform from the context-sensitive right-click menu options. You can customize your Control Center personalities using Tools→Tools Settings→Customize Control Center.

    Note - The facility to define a Control Center personality by defaults pops up each and every time you start the Control Center. You can turn off this option by deselecting the Show this window at startup time checkbox.

    DB2 Replication Center

    The DB2 Replication Center is a graphical tool that allows DBAs to quickly set up and administer all forms of data replication, including the options offered by WebSphere Replication Server. The main functions in setting up a replication environment can be performed with this tool, including:

  • Registering replication sources

  • Monitoring the replication process

  • Operating the CAPTURE and APPLY programs

  • Defining alerts

  • You can use the Replication Center to set up all kinds of DB2 replications, as shown in Figure 1–18.

    Figure 1–18The DB2 Replication Center


    DB2 Connect (Finally) Gets IBM i 7.1 Support | killexams.com real questions and Pass4sure dumps

    IBM this month announced a new release of DB2 Connect, a piece of middleware used to connect client applications running on Linux, Unix, or Windows platforms to DB2 database servers running on IBM i and z/OS. With DB2 Connect version 10.1, IBM added support for DB2 for i version 7.1. It also added a number of features for taking advantages of the latest enhancements to DB2 for z/OS.

    DB2 Connect enables client applications to create, access, update, control, and manage DB2 databases on host systems using a variety of languages, including SQL, ODBC, JDBC, DB2 APIs, SQLJ DB2 Call Level Interface (CLI), .NET, PHP, Ruby, Python, Perl, and pureQuery. The most common use of the software is serving SQL statements to DB2 on IBM i and z/OS systems, but it can also be used to join tables from multiple DB2/400 databases, including other DB2 versions and Informix, and even Oracle, SQL Server, and Sybase when coupled with that ultimate Big Blue data broker, WebSphere Information Integrator.

    The lone IBM i-related enhancement in DB2 Connect 10.1 is a biggie: support for DB2 for i running on the latest IBM i version 7.1 operating system, which shipped two years ago this month. Late support is better than no support.

    The bulk of the enhancements in DB2 Connect 10.1 focus on the various drivers to support the latest capabilities in DB2 10 for z/OS platform, which IBM shipped in October 2010. This includes: binary XML support in Java drivers; XML-related performance boosts; support for extended vector variables; temporal table support; enhanced timestamp precision; and other performance and high availability enhancements.

    This release also delivers better support for IBM tools, including WebSphere Application Server, Optim Configuration Manager, and Data Studio. Programmers will be happy to hear DB2 Connect 10.1 brings: new JDBC 4.1 capabilities for Java 7; support for the .NET 4.0 framework with Entity Framework; full integration with Visual Studio 2010; and support for migrating applications from other database vendors to DB2 for z/OS.

    IBM has also reworked its various DB2 Connect bundles, including shrinking the footprint of its Data Server (DS) Driver bundle; streamlined activation of DB2 Connect Unlimited Edition for System z; and new gateway options.

    Companies running the advanced IBM pureQuery Runtime for Linux, Unix, and Windows will see new security features, including the capability to prevent SQL injection by restricting the SQL executed by a specific application to specific SQL statements. This release also gives users the capability to convert dynamic SQL to static SQL, which improves performance and security.

    DB2 Connect 10.1 editions become available June 11. For more information on DB2 Connect 10.1, see IBM United States Software Announcement 212-076.

    RELATED STORIES

    Raz-Lee Claims IBM i Data-Access Breakthrough with DB-Gate

    DB2 Connect Gets Better Support for Stored Procedures and Triggers

    IBM Officially Announces i/OS 7.1

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    IBM's DB2 database update does time travel, gets graphic | killexams.com real questions and Pass4sure dumps

    With the launch of DB2 10.1, Big Blue is adding a slew of new features that make DB2 more useful for modern, big-data workloads.

    Depending on how you want to count it, IBM is either the world's number-two or number-three seller of database management systems, and it has a lot of secondary systems and services business that are driven off its DB2 databases.

    Notice that we said DB2 databases. IBM has three different DB2s, not just one. There's DB2 for the mainframe, DB2 for its midrange IBM i (formerly OS/400) platform, and DB2 for Linux, Unix, and Windows platforms.

    It is the latter one, known sometimes as DB2 LUW, that was revved up to the 10.1 release level on Tuesday. Concurrent with the database upgrade, IBM is also upgrading its InfoSphere Warehouse – a superset of DB2 designed for data warehousing and OLAP serving – to the 10.1 level.

    At a very high level, explains Bernie Spang, director of product strategy for database software and systems at IBM, the DB2 10.1 release is focused on two things: the challenge of coping with big data, and automating more of "the drudgery of the mechanics of the data layer" in applications.

    The update to DB2 and InfoSphere Warehouse, which both ship on April 30, is the culmination of four years of development by hundreds of engineers working around the globe from IBM's software labs. The new database also has several performance enhancements, a new data-compression method, and increased compatibility with Oracle databases to help encourage Oracle shops to make the jump.

    On the big-data front, IBM has juiced the connector that links DB2 to Hadoop MapReduce clusters running the Hadoop Distributed File System (HDFS). Spang says that the prior Hadoop connector was "rudimentary", and so coders went back to the drawing board and created a much better one that allows for data warehouses to more easily suck in data from and spit out data to Hadoop clusters, with less work on the part of database admins.

    IBM DB2 10 versus InfoSphere Warehouse 10

    IBM's DB2 10 versus InfoSphere Warehouse 10 (click to enlarge)

    The new DB2 also supports the storing of graph triples, which are used to do relationship analytics, or what is sometimes called graph analytics.

    Rather than looking through a mountain of data for specific subsets of information, as you do in a relational database or a Hadoop cluster, graph analytics walks you through all of the possible combinations of data to see how they are connected. The links between the data are what is important, and these are usually shown graphically using wire diagrams or other methods – hence the name graph analysis.

    Graph data is stored in a special format called Resource Definition Framework (RDF), and you query a data store with this data using a query language called SPARQL.

    The Apache Jena project is a Java framework for building semantic web applications based on graph data, and Apache Fuseki is the SPARQL server that processes the SPARQL queries and spits out the relationships so they can be visualized in some fashion. (Cray's new Urika system, announced in March, runs this Apache graph analysis stack on top of a massively multithreaded server.)

    Just like they imported objects and XML into the DB2 database so they could be indexed and processed natively, IBM is now bringing in the RDF format so that graph triples can be stored natively.

    As IBM explains it – not strictly grammatically, to some English majors – a triple has a noun, a verb, and a predicate, such as Tim (noun) has won (verb) the MegaMillions lottery (predicate). You can then query all aspects of a set of triples to see who else has won MegaMillions – a short list, in this case.

    In tests among DB2 10.1 early adopters, applications that used these graph triples ran about 3.5 times faster on DB2 than on the Jena TDB data store (short for triple database, presumably) with SPARQL 1.0 hitting it for queries.

    DB2 10.1 for Linux, Unix, and Windows platforms also includes temporal logic and analysis functions that allow it to do "time travel queries" – functions that IBM added to the mainframe variant of DB2 last year. By now supporting native temporal data formats inside the database, you can do AS OF queries in the past, present, and future across datasets without having to bolt this onto the side of the database.

    "This dramatically reduces the amount of application code to do bi-temporal queries," says Spang, and you can do it with SQL syntax, too. You can turn time travel query on or off for any table inside the DB2 database to do historical or predictive analysis across the data sets. RDF file format and SPARQL querying are available across all editions of DB2 10.1.

    Like other database makers, IBM is fixated on data compression techniques not only to reduce the amount of physical storage customers need to put underneath their databases, but also to speed up performance. With DB2 9.1, IBM added table compression, and with the more recent DB2 9.7 from a few years back, temporary space and indexes were compressed.

    With DB2 10.1, IBM is adding what it calls "adaptive compression", which means applying data row, index, and temp compression on the fly as best suits the needs of the workload in question.

    In early tests, customers saw as much as an 85 to 90 per cent reduction in disk-capacity requirements. Adaptive compression is built into DB2 Advanced Enterprise Server Edition and Enterprise Developer Edition, but is an add-on for an additional fee for Enterprise Server Edition.

    Performance boosts, management automation

    On the performance front, IBM's database hackers have tweaked the kernel of the database to make better use of the parallelism in the multicore, multithreaded processors that are common today, with specific performance enhancements for hash joins and queries over star schemas, queries with joins and sorts, and queries with aggregation.

    Out of the box, IBM says that DB2 10.1 will run up to 35 per cent faster than DB2 9.7 on the same iron. With all of the data compression turned on, many early customers are seeing a factor of three better performance from their databases. Which means – sorry, Systems and Technology Group – many DB2 customers are going to be able to get better performance without having to buy new iron.

    On the management front, DB2 now has integrated workload management features that can cap the percentage of total CPU capacity that DB2 is allowed to consume, with hard limits and soft limits across multiple CPUs that are sharing capacity. You can also prioritize important DB2 workloads with different classes of service level agreements.

    Database indexes now have new features such as jump scan, which optimizes buffer usage in the underlying system and cuts down on the CPU cycles that DB2 eats, as well as smart prefetching of index and data to boost the performance of the database, much as L1 caches in chips do for their processors.

    DB2 now also has a multi-temperature data management feature that knows the difference between flash-based SSDs, SAS RAID, SATA RAID, and tape or disk archive, and can automagically move database tables that are hot, warm, cold, and downright icy to the right device.

    Access control is a big deal, and DB2 10.1 now sports fine-grained row and column access controls so each user coming into a system can be locked out of any row or column of data. Now, employees only see the data they need to know, and you don't have to partition an application into different classes of users. You just do it at the user level based on database policies. This feature masks just the data you are not supposed to see.

    IBM continues to ramp up its compatibility with Oracle's PL/SQL query language for its eponymous databases, and says that with the 10.1 release, early access users are seeing an average of 98 per cent compatibility for Oracle PL/SQL queries running against DB2. That's not 100 per cent, but it is getting closer.

    Finally, as far as big features go, the other new one is called "continuous data ingest", which allows for external data feeds to continuously pump data into the database, or for the database to continuously pump into the data warehouse, without interrupting queries running on either box. This ingesting relies on bringing the data into the database and warehouse in a parallel fashion, with multiple connections, but exactly how it works is not clear to El Reg as we go to press. It seems a bit like magic.

    DB2 Express-C is free and has the time travel feature; it is capped at two processor cores and 4GB of main memory. DB2 Express adds the row and column access control, label access control (an existing feature) high availability clustering features (new with this release), and has a memory cap of 8GB and can run across four processor cores; it costs $6,490 per core.

    Workgroup Server boosts the cores to 16 and the memory to 64GB, and doesn't have the HA features. Enterprise Server has the multi-temperature data management feature and costs $30,660 per core. The top-end Advanced Enterprise Server has all the bells and whistles, including optimizations and tools to make DB2 play better in a data warehouse. Pricing for the Workgroup Server and Advanced Enterprise Server were not available at press time. ®

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