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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
: 108 true Questions

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IBM DB2 10.1 Advanced DBA

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

IBM this month announced a brand novel 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 combine edition 10.1, IBM delivered assist for DB2 for i edition 7.1. It additionally delivered a yoke of aspects for taking advantages of the newest enhancements to DB2 for z/OS.

DB2 combine makes it workable 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 convoke degree Interface (CLI), .web, Hypertext Preprocessor, Ruby, Python, Perl, and pureQuery. essentially the most average expend of the software is serving SQL statements to DB2 on IBM i and z/OS techniques, however can moreover live used to live a fragment 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 big Blue information broking service, WebSphere guidance Integrator.

The lone IBM i-connected enhancement in DB2 combine 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 usher in Java drivers; XML-connected efficiency boosts; assist for prolonged vector variables; temporal desk aid; superior timestamp precision; and different performance and tall availability enhancements.

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

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

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

DB2 combine 10.1 editions revolve into obtainable June eleven. For extra suggestions on DB2 combine 10.1, note 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 depart back and forth, receives realistic | killexams.com true Questions and Pass4sure dumps

With the launch of DB2 10.1, big Blue is adding a slew of novel facets that build 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 trade that are pushed off its DB2 databases.

be aware that they 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, yardstick on occasion as DB2 LUW, that became revved as much as the ten.1 unencumber even 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 artery for database software and methods at IBM, the DB2 10.1 free up is focused on two issues: the problem of coping with broad 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 novel database additionally has a number of efficiency enhancements, a novel statistics-compression formula, and expanded compatibility with Oracle databases to aid inspire Oracle shops to build 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 workable for for statistics warehouses to more without hardship suck in facts from and spit out information to Hadoop clusters, with less travail on the fragment of database admins.

IBM DB2 10 versus InfoSphere Warehouse 10

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

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

rather than searching through a mountain of information for inevitable subsets of advice, as you result in a relational database or a Hadoop cluster, graph analytics walks you through the entire workable combos of statistics to contemplate 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 moreover 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 moreover live visualized in some style. (Cray's novel 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 live listed and processed natively, IBM is now bringing within the RDF format so that graph triples may moreover live 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 low aspects of a set of triples to contemplate 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 sustain (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 genial judgment and analysis services that enable it to result "time commute queries" – features that IBM brought to the mainframe variant of DB2 final 12 months. by artery of now helping indigenous temporal records codecs interior the database, that you can result 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 result bi-temporal queries," says Spang, and you can result it with SQL syntax, too. you could flip time shuttle question on or off for any table inner the DB2 database to result primitive or predictive evaluation throughout the facts units. RDF file layout and SPARQL querying can live organize across low editions of DB2 10.1.

Like different database makers, IBM is fixated on facts compression techniques no longer simplest to prick back the quantity of actual storage shoppers should result 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 waft as best suits the wants of the workload in query.

In early checks, consumers noticed as a distinguished deal as an 85 to ninety per cent reduction in disk-means necessities. Adaptive compression is constructed into DB2 superior trade 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 own tweaked the kernel of the database to build enhanced expend 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 bustle 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 constituent of three enhanced efficiency from their databases. Which means – sorry, techniques and technology group – many DB2 purchasers are going to live capable of net improved performance while not having to buy novel 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 moreover prioritize censorious DB2 workloads with diverse classes of carrier stage agreements.

Database indexes now own novel 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 result for his or her processors.

DB2 now additionally has a multi-temperature facts administration characteristic that is aware of the disagreement 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 commandeer equipment.

entry control is a big 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 moreover live locked out of any row or column of facts. Now, personnel handiest note the records they deserve to live aware of, and you won't own to partition an software into diverse courses of clients. You simply result it on the consumer even based on database guidelines. This function masks simply the information you don't look to live 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 novel one is referred to as "continuous records ingest", which makes it workable 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 limpid to El Reg as they depart to press. It seems a bit of enjoy 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 bustle 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 own the HA aspects. enterprise Server has the multi-temperature information administration function and costs $30,660 per core. The properly-end advanced trade Server has the entire bells and whistles, including optimizations and tackle to build DB2 play better in an information warehouse. Pricing for the Workgroup Server and advanced trade Server had been not available at press time. ®

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

unless these days, trade analytics towards big records and the enterprise records warehouse needed to attain 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 own 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 trade 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 broad records options got here application programs that allowed enterprise analysts to expend 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 censorious 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 live finished there.

This required returning massive amounts of records to the analyst’s application, which required a configuration with gigantic quantities of memory and CPU vigor. This additionally spawned the conception of developing local facts marts to cling subsets of the warehouse and broad statistics as a artery to bustle extensive statistical calculations in the community. luckily, database administration methods (DBMSs) stepped up and delivered numerous novel 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 broad information respond (and, to a lesser extent an enterprise records warehouse), it's now indispensable to usher 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 enjoy 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 insinuate 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 charge 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 artery of depicting facts graphically, the most yardstick sample 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 indigenous calculation. It additionally simplifies SQL statements, enabling the database administrator (DBA) the opening to capture and tune analytical queries with the end of expanding performance and lowering resource usage. as an instance, if medians and percentiles are required for a specific column price, the DBA could correspond 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 artery for analyzing subtotals of a bunch of data items, with rollup being a subset of dice. for example, admiration an enterprise accounting device with assorted bills owned via each branch. to anatomize account balances across the organization an analyst wishes to calculate subtotals for each and every department, in addition to an yardstick complete. in this situation of affairs, the debts roll up to departments, which then roll as much as a grand total. This should live would becould very well live 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 equipoise 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 workable for the DBMS to result a unique tide of the statistics and fulfill the necessary calculations correctly.

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

    Account_Table

    Account_IDBalanceCustomer_IDCustomer_TypeAccount_TypeCustomer_Region...

    The closing three columns are candidates for grouping, as a trade analyst may moreover 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 live 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 equipoise in every district with subtotals for each customer category
  • rather than code numerous SQL statements for each workable rollup, the dice feature may moreover live used to accomplish this in a unique 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 result back by means of this statement is a result set of rows with the following:

  • Subtotal for every admixture of (Customer_Type, Account_Type, Customer_Region)
  • Subtotal for each admixture of (Customer_Type, Account_Type)
  • Subtotal for each and every aggregate of (Customer_Type, Customer_Region)
  • Subtotal for each and every admixture 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 trade 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 result in favor a big records respond 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 altenative is to sustain tables in each indigenous Db2 and in the IDAA. The potential of this option is to deliver assorted entry paths to a particular table, when you admiration that indigenous Db2 tables can own 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 live accomplished. An instance will assist clarify this.

    consider their Account desk described previous:

    Account_Table

     

    Account_ID

    steadiness

    Customer_ID

    Customer_Type

    Account_Type

    Customer_Region

    ...

    expect that Account_Table exists in a learning warehouse. This capability that it isn't a fragment of an operational gadget with ongoing on-line exercise and batch procedures; rather, it contains rows that are loaded once per day and remain static low over the day. Let’s moreover assume that the DBA has captured and analyzed common SQL statements submitted with the aid of trade 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 enjoy 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 live 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 live coded as-is, and the Db2 Optimizer will automatically entry the MQT instead of re-calculate the subtotals.

    summary

    in the early days of broad information, trade analysts grew accustomed to getting quick 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 complicated and required lager amounts of statistics. eventually, SQL analytical query performance grew to live 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 sunder aggregations and subtotals or different features that own been now not supported directly in SQL needed to live 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 fulfill such sunder statistical features equivalent to percentiles and cubes within the DBMS. This no longer best vastly reduces the volume of information traversing the community, it moreover gives the DBA opportunities to tune total sets of tables and applications instead of one SQL remark at a time.

     # # #

     For more tips:

    See low 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 true questions and Pass4sure dumps

    DB2 Extenders

    DB2 Extenders proffer the capacity to manipulate data outside of conventional rows and columns to embrace the manipulation of special data types (for example, spatial types that own 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 conduct of these unstructured data types and stores this information in DB2. From the developer's perspective, the DB2 Extenders materialize as seamless extensions to the database and enable the evolution of multimedia-based applications. In other words, a spatial data kind is no different than a built-in data kind that they may live 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 capacity to create spatially aware data objects and store them within your DB2 database, along with other spatially related objects enjoy (LAT/LONG) coordinates and more. Almost low industries could profit 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 expend this technology for flood modest identification, the retail industry for billboard locations, and more. This seems evident when you admiration that almost low data has some sort of spatial component to it: they low own an address, merchandise in a warehouse has a stock location, and so on.

    The trade profit 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 fulfill 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 frontier 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 enjoy 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 fragment 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 live particularly advantageous in Internet applications where performance is an primary factor. The DB2 NSE can add the power of quick 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 quick-witted artery of searching through such documents.

    Additionally, the DB2 NSE provides a wealthy set of XML searching capabilities with advanced search features enjoy 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 moreover gives you the capacity to shred and store XML in its component parts as columns in multiple tables. In either case, indexes can live defined over the elements or attributes of an XML document for quick retrieval. Furthermore, text and fragment search can live enabled on the XML column or its decomposed parts via the DB2 Net Search Extender. The DB2 XML Extender can moreover assist 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 low DB2 9 data servers. Indeed, this can antecedent confusion since the DB2 XML Extender is shipped for free in DB2 9. You should admiration the DB2 XML Extender as stabilized technology. In other words, it is no longer being enhanced and shouldn't live 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 big object. When you expend this technology to persist XML data, you own to build sedate trade-offs with respect to performance, flexibility, and so on. In addition, you own to expend specialized functions to implement Spathe searches, and data types are absent-minded from basis DB2 data types. Quite simply, the artery 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 live made when storing your XML data. For example, to generate XML documents from relational tables, you simple expend the SQL/XML API instead of the cumbersome DB2 XML Extender functions. You can validate XML documents against Sods instead of only document kind definitions (Ds) as is the case with the DB2 XML Extender, and more. They strongly recommend this feature for most of your XML-based applications.

    DB2 Administration

    DB2 DBAs own a number of graphical-based tools they can expend to manage and administer DB2 data servers. Alternatively, a DBA can moreover expend 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 hub is the central point of administration for DB2. The Control hub provides DBAs with the tools necessary to fulfill typical database administration tasks. It allows facile access to other server administration tools, gives a limpid overview of the entire system, enables remote database management, and provides step-by-step assistance for complicated tasks.

    Figure 1–17The DB2 Control Center

    The low Systems kick represents both local and remote data servers. To parade low the DB2 systems that your system knows about, expand the kick tree by clicking on the plus note (+) next to low Systems. In pattern 1–17, you can note 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 kick are shown in the Contents Pane.

    The main components of the Control hub are:

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

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

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

  • Contents Pane — This is organize on the right side of the Control hub window and contains the objects that belong or correspond to the kick 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 moreover live selected in the View menu.

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

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

  • The Control hub moreover comes with personality control that you can expend to adjust the view and functions available from the Control Center's tree view of your data server. For example, you can restrict the kick smart view to present just Tables or Views, as well as restrict the actions you can fulfill from the context-sensitive right-click menu options. You can customize your Control hub personalities using Tools→Tools Settings→Customize Control Center.

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

    DB2 Replication Center

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

  • Registering replication sources

  • Monitoring the replication process

  • Operating the CAPTURE and APPLY programs

  • Defining alerts

  • You can expend the Replication hub to set up low kinds of DB2 replications, as shown in pattern 1–18.

    Figure 1–18The DB2 Replication Center


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

    IBM this month announced a novel 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 moreover 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 convoke even Interface (CLI), .NET, PHP, Ruby, Python, Perl, and pureQuery. The most common expend of the software is serving SQL statements to DB2 on IBM i and z/OS systems, but it can moreover live used to combine tables from multiple DB2/400 databases, including other DB2 versions and Informix, and even Oracle, SQL Server, and Sybase when coupled with that ultimate broad 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 tall availability enhancements.

    This release moreover delivers better support for IBM tools, including WebSphere Application Server, Optim Configuration Manager, and Data Studio. Programmers will live cheerful to hear DB2 Connect 10.1 brings: novel 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 moreover 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 novel gateway options.

    Companies running the advanced IBM pureQuery Runtime for Linux, Unix, and Windows will note novel security features, including the capability to forestall SQL injection by restricting the SQL executed by a specific application to specific SQL statements. This release moreover gives users the capability to transform 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, note 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 realistic | killexams.com true questions and Pass4sure dumps

    With the launch of DB2 10.1, broad Blue is adding a slew of novel features that build 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 trade that are driven off its DB2 databases.

    Notice that they 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 even on Tuesday. Concurrent with the database upgrade, IBM is moreover upgrading its InfoSphere Warehouse – a superset of DB2 designed for data warehousing and OLAP serving – to the 10.1 level.

    At a very tall 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 broad 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 evolution by hundreds of engineers working around the globe from IBM's software labs. The novel database moreover has several performance enhancements, a novel data-compression method, and increased compatibility with Oracle databases to assist cheer Oracle shops to build 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 travail on the fragment of database admins.

    IBM DB2 10 versus InfoSphere Warehouse 10

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

    The novel DB2 moreover supports the storing of graph triples, which are used to result relationship analytics, or what is sometimes called graph analytics.

    Rather than looking through a mountain of data for specific subsets of information, as you result in a relational database or a Hadoop cluster, graph analytics walks you through low of the workable combinations of data to note 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 live visualized in some fashion. (Cray's novel Urika system, announced in March, runs this Apache graph analysis stack on top of a massively multithreaded server.)

    Just enjoy they imported objects and XML into the DB2 database so they could live indexed and processed natively, IBM is now bringing in the RDF format so that graph triples can live 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 low aspects of a set of triples to note 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 moreover includes temporal logic and analysis functions that allow it to result "time travel queries" – functions that IBM added to the mainframe variant of DB2 terminal year. By now supporting indigenous temporal data formats inside the database, you can result 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 result bi-temporal queries," says Spang, and you can result it with SQL syntax, too. You can revolve time travel query on or off for any table inside the DB2 database to result historical or predictive analysis across the data sets. RDF file format and SPARQL querying are available across low 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 result underneath their databases, but moreover to accelerate 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 waft 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 own tweaked the kernel of the database to build better expend 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 bustle up to 35 per cent faster than DB2 9.7 on the selfsame iron. With low 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 live able to net better performance without having to buy novel 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 arduous limits and soft limits across multiple CPUs that are sharing capacity. You can moreover prioritize primary DB2 workloads with different classes of service even agreements.

    Database indexes now own novel 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 result for their processors.

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

    Access control is a broad deal, and DB2 10.1 now sports fine-grained row and column access controls so each user coming into a system can live locked out of any row or column of data. Now, employees only note the data they need to know, and you don't own to partition an application into different classes of users. You just result it at the user even based on database policies. This feature masks just the data you are not suppositious 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 broad features go, the other novel 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 limpid to El Reg as they depart to press. It seems a bit enjoy 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) tall availability clustering features (new with this release), and has a memory cap of 8GB and can bustle 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 own 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 low the bells and whistles, including optimizations and tools to build 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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    References :


    weSRCH : https://www.wesrch.com/business/prpdfBU1HWO000VVIV
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    Wordpress : http://wp.me/p7SJ6L-D0
    Scribd : https://www.scribd.com/document/359012091/Pass4sure-C2090-614-Practice-Tests-with-Real-Questions
    Issu : https://issuu.com/trutrainers/docs/c2090-614
    Dropmark-Text : http://killexams.dropmark.com/367904/12088822
    Blogspot : http://killexams-braindumps.blogspot.com/2017/11/never-miss-these-c2090-614-questions.html
    Youtube : https://youtu.be/ChhidoU0A58
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    Google+ : https://plus.google.com/112153555852933435691/posts/YKBpYMP9PW2?hl=en
    publitas.com : https://view.publitas.com/trutrainers-inc/dont-miss-these-ibm-c2090-614-dumps
    Calameo : http://en.calameo.com/books/00492352647c3df15ba84
    Box.net : https://app.box.com/s/yd8hfrsaj90u9v055es30qpfoiodiow1
    zoho.com : https://docs.zoho.com/file/3y7xk26cc7d017a0f4117bdb0bae52c7f1149











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