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000-516 DB/2 Administration for OS/390

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000-516 exam Dumps Source : DB/2 Administration for OS/390

Test Code : 000-516
Test title : DB/2 Administration for OS/390
Vendor title : IBM
: 118 existent Questions

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IBM DB/2 Administration for OS/390

the course to derive DB2 admin certified | killexams.com existent Questions and Pass4sure dumps

i am drawn to doing certification in DB2 administration for OS/390. i want to grasp the field, now not just derive the certification.

neatly, the most advantageous fashion to grasp any discipline is with the aid of doing it. So, with that in intellect, breathe certain to secure a position where you fill got entry to DB2 and requisite to labor with it to function your job. but, i'm guessing that your goal is to derive a job and that you just want to derive certified to attain one. if that is the case, then there are some steps that you would breathe able to take. first off, believe acquiring here books for examine and reference: DB2 Developer's e book, 5th version through Craig S. Mullins Db2 For The Z/os version eight Certification by course of Susan Lawson DB2 regularly occurring Database for OS/390 v7.1 utility Certification e bespeak through Susan Lawson bethink to likewise download, and evaluation, the entire DB2 for z/OS manuals from the IBM net website. moreover, always review the in-depth technical articles published by course of IBM at its developerWorks website. different decent web sites to bookmark and assessment consist of Search390.com, SearchDatabase.com, dbazine.com, DB2 for OS390, and DB2 times. concerning your eventual question, i would inform that the most fulfilling approach to reap my DBA ebook is by course of amazon.com.

Editor's observe: Do you accept as actual with this knowledgeable's response? in case you fill more to share, post it in a single of their .VO7aaqqaAFk.0@/search390>discussion boards.


IBM Db2 query Optimization the usage of AI | killexams.com existent Questions and Pass4sure dumps

In September 2018, IBM introduced a brand new product, IBM Db2 AI for z/OS. This synthetic intelligence engine displays statistics entry patterns from executing SQL statements, uses desktop studying algorithms to select top-quality patterns and passes this guidance to the Db2 query optimizer for exhaust by using subsequent statements.

desktop getting to know on the IBM z Platform

In may additionally of 2018, IBM introduced edition 1.2 of its desktop gaining knowledge of for z/OS (MLz) product. here is a hybrid zServer and cloud utility suite that ingests efficiency records, analyzes and builds models that signify the fitness repute of a number of symptoms, monitors them over time and offers true-time scoring capabilities.

a number of aspects of this product providing are geared toward helping a neighborhood of model builders and executives. for example:

  • It helps diverse programming languages such as Python, Scala and R. This enables data modelers and scientists to exhaust a language with which they're generic;
  • A graphical person interface known as the visible mannequin Builder publications mannequin developers with out requiring tremendously-technical programming capabilities;
  • It contains varied dashboards for monitoring model results and scoring capabilities, as well as controlling the system configuration.
  • This computer discovering suite was originally geared toward zServer-based analytics functions. one of the first obtrusive decisions changed into zSystem performance monitoring and tuning. system management Facility (SMF) facts that are automatically generated by the working system give the uncooked records for materiel resource consumption similar to faultfinding processor utilization, I/O processing, reminiscence paging etc. IBM MLz can collect and shop these statistics over time, and build and educate fashions of device conduct, rating these behaviors, identify patterns now not effectively foreseen by course of humans, augment key efficiency indications (KPIs) and then feed the model results returned into the device to fill an consequence on gadget configuration changes that may enhance efficiency.

    The next step changed into to enforce this suite to dissect Db2 efficiency facts. One answer, known as the IBM Db2 IT Operational Analytics (Db2 ITOA) solution template, applies the computer getting to know expertise to Db2 operational data to benefit an figuring out of Db2 subsystem fitness. it may well dynamically build baselines for key performance indications, deliver a dashboard of those KPIs and give operational workforce precise-time perception into Db2 operations.

    whereas customary Db2 subsystem efficiency is a vital ingredient in overall utility health and efficiency, IBM estimates that the DBA encourage personnel spends 25% or more of its time, " ... combating access route problems which occasions efficiency degradation and service fill an consequence on.". (See Reference 1).

    AI comes to Db2

    trust the plight of simultaneous DBAs in a Db2 ambiance. In trendy IT world they must assist one or greater gigantic information applications, cloud software and database services, application installing and configuration, Db2 subsystem and application performance tuning, database definition and administration, catastrophe recovery planning, and more. question tuning has been in being due to the fact the origins of the database, and DBAs are always tasked with this as well.

    The heart of query route analysis in Db2 is the Optimizer. It accepts SQL statements from functions, verifies authority to entry the information, reports the places of the objects to breathe accessed and develops a list of candidate facts entry paths. These access paths can consist of indexes, table scans, a considerable number of table breathe Part of strategies and others. within the statistics warehouse and large data environments there are constantly further decisions purchasable. One of those is the being of summary tables (from time to time referred to as materialized question tables) that comprise pre-summarized or aggregated records, as a result allowing Db2 to preclude re-aggregation processing. an extra option is the starjoin entry route, typical in the records warehouse, where the order of desk joins is modified for performance factors.

    The Optimizer then reviews the candidate access paths and chooses the access course, "with the lowest charge." can saturate in this context capacity a weighted summation of resource usage together with CPU, I/O, reminiscence and other resources. eventually, the Optimizer takes the bottom can saturate entry course, stores it in reminiscence (and, optionally, in the Db2 directory) and starts off entry direction execution.

    huge information and records warehouse operations now consist of application suites that allow the enterprise analyst to exhaust a graphical interface to build and manipulate a miniature records mannequin of the facts they want to analyze. The packages then generate SQL statements in response to the users’ requests.

    The issue for the DBA

    in order to Do respectable analytics to your varied records retailers you requisite a very edifying realizing of the statistics requirements, an knowing of the analytical services and algorithms purchasable and a excessive-performance data infrastructure. alas, the number and site of information sources is increasing (both in dimension and in geography), statistics sizes are transforming into, and functions proceed to proliferate in quantity and complexity. How should IT managers aid this ambiance, notably with the most skilled and ripen personnel nearing retirement?

    take note likewise that a large a Part of decreasing the overall can saturate of ownership of these methods is to derive Db2 functions to elope quicker and more efficiently. This always interprets into the usage of fewer CPU cycles, doing fewer I/Os and transporting less information throughout the network. since it is commonly difficult to even identify which applications may handicap from performance tuning, one strategy is to automate the detection and correction of tuning considerations. here's the space computer studying and synthetic intelligence can breathe used to outstanding impact.

    Db2 12 for z/OS and simulated Intelligence

    Db2 version 12 on z/OS makes exhaust of the desktop learning facilities mentioned above to accumulate and sustain SQL question textual content and entry route details, as well as exact performance-connected historical suggestions equivalent to CPU time used, elapsed times and consequence set sizes. This offering, described as Db2 AI for z/OS, analyzes and stores the records in computer researching models, with the model evaluation effects then being scored and made attainable to the Db2 Optimizer. The next time a scored SQL observation is encountered, the Optimizer can then exhaust the mannequin scoring statistics as enter to its access direction alternative algorithm.

    The consequence may noiseless breathe a discount in CPU consumption as the Optimizer uses mannequin scoring enter to opt for more desirable access paths. This then lowers CPU fees and speeds application response instances. a significant capabilities is that the exhaust of AI utility does not require the DBA to fill data science skills or profound insights into query tuning methodologies. The Optimizer now chooses the ultimate access paths based mostly now not only on SQL query syntax and records distribution facts but on modelled and scored historic efficiency.

    This will likewise breathe primarily crucial if you sustain statistics in diverse places. as an example, many analytical queries against huge statistics require concurrent access to positive information warehouse tables. These tables are frequently referred to as dimension tables, and they contain the statistics points always used to manage subsetting and aggregation. for instance, in a retail environment believe a table called StoreLocation that enumerates each redeem and its zone code. Queries against shop sales information might likewise want to combination or summarize income by course of area; therefore, the StoreLocation table can breathe used by course of some massive facts queries. in this atmosphere it is common to select the dimension tables and replica them always to the massive facts application. within the IBM world this region is the IBM Db2 Analytics Accelerator (IDAA).

    Now suppose about SQL queries from each operational functions, statistics warehouse clients and gigantic records enterprise analysts. From Db2's point of view, all these queries are equal, and are forwarded to the Optimizer. youngsters, within the case of operational queries and warehouse queries they should absolutely breathe directed to entry the StoreLocation desk in the warehouse. nevertheless, the question from the enterprise analyst in opposition t massive statistics tables may noiseless probably entry the replica of the desk there. This consequences in a proliferations of talents entry paths, and extra labor for the Optimizer. happily, Db2 AI for z/OS can supply the Optimizer the tips it needs to accomplish sage access direction decisions.

    the course it Works

    The sequence of routine in Db2 AI for z/OS (See Reference 2) is commonly privilege here:

  • during a bind, rebind, establish together or clarify operation, an SQL commentary is handed to the Optimizer;
  • The Optimizer chooses the records entry route; because the alternative is made, Db2 AI captures the SQL syntax, entry route alternative and query performance facts (CPU used, etc.) and passes it to a "gaining knowledge of project";
  • The researching project, which will likewise breathe done on a zIIP processor (a non-ordinary-aim CPU core that doesn't factor into software licensing fees), interfaces with the computing device researching application (MLz model services) to sustain this counsel in a model;
  • because the volume of records in each and every mannequin grows, the MLz Scoring service (which likewise can breathe done on a zIIP processor) analyzes the mannequin statistics and scores the behavior;
  • all over the subsequent bind, rebind, establish together or explain, the Optimizer now has access to the scoring for SQL fashions, and makes acceptable alterations to entry path selections.
  • There are likewise a lot of consumer interfaces that provide the administrator visibility to the popularity of the collected SQL commentary performance records and mannequin scoring.

    summary

    IBM's desktop studying for zOS (MLz) providing is being used to extremely edifying consequence in Db2 edition 12 to enhance the performance of analytical queries as well as operational queries and their associated functions. This requires management consideration, as you should check that your traffic is ready to devour these ML and AI conclusions. How will you measure the charges and merits of the exhaust of desktop getting to know? Which IT usher body of workers fill to breathe tasked to reviewing the outcomes of mannequin scoring, and perhaps approving (or overriding) the consequences? How will you review and warrant the assumptions that the utility makes about entry route choices?

    In different phrases, how well were you watchful your facts, its distribution, its integrity and your current and proposed access paths? this may assess where the DBAs disburse their time in supporting analytics and operational application performance.

    # # #

    Reference 1

    John Campbell, IBM Db2 extraordinary EngineerFrom "IBM Db2 AI for z/OS: enhance IBM Db2 utility efficiency with machine gaining knowledge of"https://www.worldofdb2.com/movements/ibm-db2-ai-for-z-os-raise-ibm-db2-software-performance-with-ma

    Reference 2

    Db2 AI for z/OShttps://www.ibm.com/guide/knowledgecenter/en/SSGKMA_1.1.0/src/ai/ai_home.html

    See all articles via Lockwood Lyon


    Object-Relational Programming with DB2 | killexams.com existent Questions and Pass4sure dumps

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    IBM DB2 V7 for OS/390 picture, Audio, and Video Extenders Administration and Programming – SES1-2199-0

    IBM DB2 V7 for OS/390 XML Extender Administration and Programming – SES1-2201-00

    IBM DB2 V7 for OS/390 textual content Extender Administration and Programming – SES1-2200-00


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    DB/2 Administration for OS/390

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    Basic SQL Coding for DB2 Universal Database for OS/390 | killexams.com existent questions and Pass4sure dumps

    Take a recognize at the four primary statements of DML: Select, Update, Insert, and Delete. You will learn the function each of these can play in your efforts to master DB2. You will likewise recognize at various aspects of SQL, a necessary language to understand though the comprehension flat will vary depending on the user's activity.

    This chapter is from the bespeak 

    In the previous chapter, they discussed the definitions of various database objects using the Data Definition Language (DDL). In this chapter, they start manipulating the database objects using the portion of SQL known as Data Manipulation Language (DML). They will breathe populating (inserting) data into the database and retrieving the data using many powerful methods. Depending on the sophistication of the database users, they can exhaust SQL to query the database. The majority of the SQL statements within a DB2 application involve DML statements. Therefore, application developers must understand the various methods of inserting, updating, and retrieving data from the database. They will start with simple retrieval statements and gradually interlard more complicated methods of data manipulation. The DB2 Certification database will breathe used for most of the examples. There are four main DML SQL statements they consider: SELECT, INSERT, UPDATE, and DELETE.

    SQL is based on mathematical principles, specifically on set theory and relational algebra. The data is stored in the database as unordered sets of data records. SQL is a set-oriented language, and many of its language elements are directly related to relational algebraic terms, such as permutation, projection, restriction, and join.

    A set of data is represented in a DB2 database as a table or a view and is stored in a DB2 table without admiration to order. To retrieve data in a particular order, an ORDER BY phrase must breathe added to a SELECT statement. Similarly, if the data is to breathe grouped, then a GROUP BY phrase must breathe added to the statement.

    Now, let's review the DB2CERT database design defined in the previous chapter and manipulate data using various SQL statements. There are three main tables: CANDIDATE, TEST, and TEST_CENTER. Each table represents a set of records that correspond to a test candidate (person), a test, and a test heart (location).

    There is an associative table, known as the TEST_TAKEN table, that is used to reflect the relationships among the three main tables. The TEST_TAKEN table is used to schedule the test candidates and likewise to maintain their test scores.

    NOTE

    The longest SQL statement is 32,765 bytes.

    Remember that to execute any operation, the user must fill the necessary privileges.

    Retrieving the Entire Table

    The most basic of all retrieval command involves the SELECT statement with no operators other than the title of the table. This SQL statement retrieves all of the candidates who fill taken a DB2 Certification exam. The information requested is contained in the table TEST_TAKEN.

    SELECT * FROM db2cert.test_taken

    SQL is a data access language that consists of language statements and clauses. There are many optional clauses that can breathe used to modify the output. The output of a SELECT statement is known as a result set or result table. The results from the SELECT statement are shown next. In this example, using an asterisk or star character (*) for column selection, the columns will breathe returned to the user in the order in which they are defined in the table.

    CID TCID NUMBER DATE_TAKEN START_TIME FINISH_TIME SCORE PASS_FAIL SEAT_NO --- ---- ------ ---------- ---------- ----------- ----- --------- ------- 111 TX01 500 01/01/2000 11:30:00 12:30:00 65 Y 1 111 TX01 501 02/02/2000 10:30:00 11:45:00 73 Y 1 111 TX01 502 03/03/2000 12:30:00 13:30:00 67 Y 1 222 TR01 500 01/01/2000 14:00:00 15:30:00 55 N 2 222 TR01 502 01/02/2000 09:00:00 10:15:00 53 N 2 222 TR01 502 02/18/2000 10:00:00 11:30:00 75 Y 2 333 TX01 500 03/01/2000 11:30:00 13:00:00 82 Y 2 333 TX01 501 12/29/2000 14:00:00 - - - 1 333 TX01 502 03/02/2000 14:00:00 14:30:00 92 Y 1 9 record(s) selected.

    In SQL, the * is used to betoken that all columns of a table are being referenced. In this example, the SQL statement refers to all of the columns defined for the DB2CERT.TEST_TAKEN table. If the table is altered and a new column is added to the table definition, the result set would contain the new column.

    NOTE

    Adding a new column to an existing table will result in default values being populated for the existing rows.

    Since the output of the SQL statement using * character varies according to the table definition, it is recommended that you specify all of the column names you want to survey in the SELECT statement. They could fill obtained the identical result as the statement using SELECT * with the following SQL statement.

    SELECT cid, tcid, number,date_taken,start_time, finish_time,score,seat_no FROM db2cert.test_taken;

    NOTE

    The * character is used to refer to all of the columns defined for a table. The order of the columns in the result table is the identical order as specified in the CREATE TABLE or CREATE VIEW statement.

    What is returned to the user is known as the result set. If the result set is large it is advisable to breathe certain to filter the data using a WHERE predicate.

    The FROM clause is required for the DML SQL statement, since it describes the location (table or view) of the data. Their instance references a single table called DB2CERT.TEST_TAKEN. The SELECT and FROM clauses are required in all data retrieval statements. The list of columns following the SELECT keyword is referred to as the select list.

    Projecting Columns from a Table

    Projection is a relational operation that allows you to retrieve a subset of the defined columns from a table. The next instance restricts the output from the SELECT command so that only the candidate ID, test center, and test number attributes from the TEST_TAKEN table are shown.

    SELECT cid,tcid,number FROM db2cert.test_taken

    The output of this SELECT statement is shown below.

    CID TCID NUMBER --- ---- ------ 111 TX01 500 111 TX01 501 111 TX01 502 222 TR01 500 222 TR01 502 222 TR01 502 333 TX01 500 333 TX01 501 333 TX01 502 9 record(s) selected.

    The order of the columns in the result table will always match the order in the select list. The order of the columns as they were defined in the CREATE TABLE or CREATE VIEW statement is ignored when a select list is provided in the SQL statement. In this example, the order of the columns is similar to the order in the CREATE TABLE statement, since the CID column was defined prior to TCID and NUMBER columns.

    Changing the Order of the Columns

    Permutation is the relational operation that allows you to change the order of the columns in your result table. Permutation is used every time you select columns in an order different than the order defined in the CREATE TABLE statement. For example, to pomp the test heart ID prior to the candidate IDs and the test number, you could execute the following:

    SELECT tcid,cid,number FROM db2cert.test_taken

    The result of this SELECT statement specifies a select list in a different order than was defined in the table definition.

    TCID CID NUMBER ---- --- ------ TX01 111 500 TX01 111 501 TX01 111 502 TR01 222 500 TR01 222 502 TR01 222 502 TX01 333 500 TX01 333 501 TX01 333 502 9 record(s) selected.

    NOTE

    We refer to the output of a SELECT statement as the result table because the output of all SELECT statements can breathe considered a relational table.

    Restricting Rows from a Table

    Restriction is a relational operation that will filter the resulting rows of a table. Restriction can breathe accomplished through the exhaust of predicates defined in a SQL WHERE clause. To restrict the result set, they requisite to add a WHERE clause to the SQL statement.

    NOTE

    A predicate is a condition placed on the data. The result of the condition is TRUE, FALSE, or UNKNOWN.

    The WHERE clause specifies conditions or predicates that must breathe evaluated by DB2 before the result table is returned to the discontinue user. There are many convincing types of predicates that can breathe used. In the following example, the equality (=) predicate is used to restrict the records to only those candidates who fill taken a DB2 Certification test at the test heart TR01.

    SELECT tcid,cid FROM db2cert.test_taken WHERE tcid ='TR01'

    The WHERE clause likewise accepts other comparison operators, such as greater than (>), less than (<), greater than or equal to (>=), less than or equal to (<=), and not equal to (<>).This statement is an instance of a basic predicate. A basic predicate compares two values. In addition, more complicated predicates, such as LIKE, BETWEEN, and IN, are likewise convincing and will breathe discussed later.

    NOTE

    Trying to execute this instance SQL statement will result in a data character compatibility error, because the column TCID is defined with a user-defined data character (UDT).

    Predicate Evaluation for UDTs

    The column TCID was defined as a user-defined data type. To accomplish the comparison in the WHERE clause valid, a casting function needs to breathe used. This is not mandatory if the comparison is to a literal or host variable. This technique is however demonstrated below:

    SELECT tcid, cid FROM db2cert.test_taken WHERE tcid=CAST('TR01' AS db2cert.center_id)

    Predicate evaluation requires that the data types breathe compatible (same data character or a compatible data type). They can accomplish the data character conversion (cast) using one of two methods:

  • Use the CAST expression.
  • Use a casting function.
  • Refer to Chapter 15, "Object Relational Programming," for more information on casting for UDTs.

    NOTE

    Although not always mandatory, casting is recommended to ensure compatible data types are compared, including length and scale. This allows DB2 to resolve these as indexable rather than stage 2 predicates.

    Restricting Rows Using Multiple Conditions

    It is viable to combine multiple conditions (predicates) in a single SQL statement. The predicates can breathe combined using Boolean operators, such as the AND or OR operators. These operators allow you to combine multiple conditions in a single SQL statement. The order of the predicate evaluation will not influence the result set (known as set closure).

    The next instance retrieves the records for the test candidates who took a test at test heart TR01 and achieved a score greater than 65. The rows that meet the predicates are known as the qualifying rows. The following instance is an SQL statement using multiple predicates:

    SELECT tcid,cid,score FROM db2cert.test_taken WHERE tcid= CAST('TR01' AS db2cert.center_id) AND score > 65 Selecting Columns from Multiple Tables

    There are basically two operations that combine columns from multiple tables in a single SQL statement. These operations are

    Cartesian Product

    A Cartesian product is a relational operation that will merge all the values from one table with all the values from another table. This operation is not used frequently because the result table can breathe very large. The number of rows in the result table is always equal to the product of the number of rows in the qualifying rows for each of the tables being accessed.

    NOTE

    The DB2 optimizer may elect to utilize a Cartesian product of unrelated tables if this is deemed to breathe an efficient fashion of accessing multiple tables. An instance would breathe two single-row tables that are joined with a large table. The cross-product of 1 ∴ 1 = 1; thus the large table access is deferred as late as possible, with a potential augment in the restrictive predicates that can breathe applied without incurring the overhead of a large Cartesian result. This fashion of table access is typical in processing queries against a star schema data model.

    The following instance is a Cartesian product of all test numbers and test names from the TEST table, with all candidates from the TEST_TAKEN table. First, select from the TEST table.

    SELECT number, title FROM db2cert.test NUMBER NAME ------ -------------------------------------------------- 500 DB2 Fundamentals 501 DB2 Administration 502 DB2 Application Development 3 record(s) selected. Next select of all candidates from the test_taken table. SELECT cid,tcid FROM db2cert.test_taken CID TCID --- ---- 222 TR01 222 TR01 222 TR01 111 TX01 111 TX01 111 TX01 333 TX01 333 TX01 333 TX01 9 record(s) selected.

    Then combine the two tables to contour a Cartesian product result table.

    SELECT db2cert.test_taken.number,cid,tcid FROM db2cert.test_taken,db2cert.test NUMBER CID TCID ------ --- ---- 500 111 TX01 501 111 TX01 502 111 TX01 500 222 TR01 502 222 TR01 502 222 TR01 500 333 TX01 501 333 TX01 502 333 TX01 500 111 TX01 501 111 TX01 502 111 TX01 500 222 TR01 502 222 TR01 502 222 TR01 500 333 TX01 501 333 TX01 502 333 TX01 500 111 TX01 501 111 TX01 502 111 TX01 500 222 TR01 502 222 TR01 502 222 TR01 500 333 TX01 501 333 TX01 502 333 TX01 27 record(s) selected.

    There are two tables referenced in the FROM clause of this query. The tables are separated by commas. There is no relationship expression in the WHERE clause. This character of query results in a Cartesian product.

    The result table is a representation of all viable combinations of the input tables. The TEST table has three rows, and the TEST_TAKEN table has nine rows. Therefore, the SELECT statement shown above returns 27 rows. Note the first column title in this query. It is necessary to fully qualify the column title by providing the schema title and table title with the column title because this column exists in both the TEST table and TEST_TAKEN table. In this case, they needed to specify that the NUMBER column is to breathe retrieved from the DB2CERT.TEST_TAKEN table and not from the DB2CERT.TEST table.

    By adding a predicate to a Cartesian product SQL query, the result table can depict a more useful representation of the data. In the instance below, the query represents all of the tests that were taken by the candidate whose ID is 111.

    SELECT db2cert.test_taken.number,cid,tcid FROM db2cert.test_taken,db2cert.test WHERE cid='111' NUMBER CID TCID ------ --- ---- 500 111 TX01 500 111 TX01 500 111 TX01 501 111 TX01 501 111 TX01 501 111 TX01 502 111 TX01 502 111 TX01 502 111 TX01 9 record(s) selected.

    Adding a WHERE clause to your query does not always provide the desired result. In the instance shown above, you want to know all of the tests that were taken by the candidate whose ID is 111, and the query returns nine rows. But they know from previous queries that the candidate took only three tests. The query in the instance above has a WHERE clause to filter out the candidate whose ID is 111 from the TEST_TAKEN table, but there was no filter on the TEST_CENTER table. Therefore, the result of the query would always breathe a multiple of the number of testing centers. Usually, when multiple tables are referenced, you should include a cross-table relationship using a table merge or combine method, as shown in the following example. They will examine table combine methods further in the next section.

    SELECT db2cert.test_taken.number,cid,tcid FROM db2cert.test_taken,db2cert.test WHERE cid= '111' AND db2cert.test_taken.number=db2cert.test.number NUMBER CID TCID ------ --- ---- 500 111 TX01 501 111 TX01 502 111 TX01 3 record(s) selected.

    To avoid data redundancy, it is recommended that the database tables breathe normalized. Following a normalization process, a number of related tables will exist. To meet some of the required queries, the tables must breathe reconstructed. The tables are reconstructed temporarily, using a table combine strategy to bear a single-result table.

    The result tables in the previous examples usually provided candidate ID numbers and not the complete title of the test candidates. The candidate IDs are stored in the TEST_TAKEN table, and the replete names are stored in the CANDIDATE table. To obtain the title of a candidate, the data must breathe retrieved from the CANDIDATE table, using a relationship or combine strategy.

    Consider an instance that will list the names and phone numbers of candidates who were registered to select a DB2 Certification test in 2000. To accomplish this, they requisite to select data from two different tables:

  • db2cert.candidate
  • db2cert.test_taken
  • Let's retrieve a list of candidate names, phone numbers, and IDs from the CANDIDATE table. The candidate names were stored in multiple columns to allow for simple retrieval by eventual name.

    SELECT fname,initial,lname,hphone,cid FROM db2cert.candidate

    The output of this instance follows. Pay special attention to the values in the CID column. It will breathe used as the combine column in the next example.

    FNAME INITIAL LNAME HPHONE CID -------- ------- ---------- ---------- --- Bill B Wong 1115551234 111 George Baklarz 2226543455 222 Susan M Visser 4442314244 333 Glen R Sheffield 5552143244 444 Jim G Stittle 6662341234 555 Kevin W Street 7773142134 666 Bert F Nicol 8886534534 777 Paul C Zikopoulos 9992112212 888 8 record(s) selected.

    Now, let's retrieve the ID numbers of those candidates who were registered to select the test in 2000.

    SELECT distinct cid FROM db2cert.test_taken WHERE YEAR(date_taken) = 2000 CID --- 222 111 333 3 record(s) selected.

    The candidate IDs in the TEST_TAKEN table must correspond to a candidate ID in the CANDIDATE table because of the declarative referential integrity constraints. The parent table in the relationship is the CANDIDATE table and the child table (dependent table) is the TEST_TAKEN table.

    The result table from the above query does not include the test candidate 444, since that candidate did not fill a test scheduled for 2000. They requisite to combine the two result tables based on the candidate ID values. This column is known as the combine column.

    NOTE

    Query performance can significantly ameliorate if the combine columns are appropriately indexed.

    The following single query will meet the end-user requirement.

    SELECT distinct fname,initial,lname,hphone FROM db2cert.test_taken,db2cert.candidate WHERE YEAR(date_taken) = 2000 AND db2cert.test_taken.cid=db2cert.candidate.cid

    A table combine requires a predicate that includes an expression based on columns from the tables referenced in the FROM clause. This is known as a combine predicate. The FROM clause has not changed from the Cartesian product examples. The only incompatibility is in the combine predicate (test_taken.cid = candidate.cid).

    NOTE

    An alternative contour of the FROM clause for joins involves explicitly coding the combine keyword between the tables (rather than using a comma) and coding the combine predicates in the ON clause rather than in the WHERE clause. This fashion of coding will breathe covered in more detail in Chapter 4, "Advanced SQL Coding."

    The table names needed to breathe explicitly stated because there is a column named CID in both of the referenced tables. When multiple tables are being accessed in a single query, any selected columns that occur in more than one table must breathe qualified with the table name.

    NOTE

    An oversight will occur if the columns being referenced are abstruse (not properly qualified).

    The maximum number of base tables that can breathe in a single SQL statement is 225; however, you are limited to 15 tables in a combine (the FROM clause).

    NOTE

    The 15-table circumscribe can breathe increased by updating the macro SPRMMXT to a value greater than 15.

    This kind of combine operation shown in the above instance is likewise known as an inner join. An inner combine displays only the rows that are present in both of the joined tables.

    Using Correlation Names

    If each of the columns needed to breathe fully qualified with the table name, such as tableschema.tablename.columnname, the queries would become very large and cumbersome to labor with. Fortunately, there is an easier course to qualify the abstruse columns resulting from a multitable SELECT statement.

    The columns can breathe qualified using a correlation name. A correlation title is a temporary alias for the tables referenced in an SQL statement. They rewrite the previous query using correlated names as follows:

    SELECT distinct fname,initial,lname,hphone FROM db2cert.test_taken tt, db2cert.candidate c WHERE YEAR(date_taken) = 2000 AND tt.cid = c.cid

    The correlation title immediately follows the title of the table as stated in the FROM clause. In this example, the correlated title for the TEST_TAKEN table is tt, and the correlated title for the CANDIDATE table is c.

    NOTE

    Correlation names can breathe optionally prefixed with the AS keyword, such as DB2CERT.CANDITATE AS C. This is purely for readability.

    The correlated names are accessible within the SQL statement only. Following the execution of the SQL statement, the correlation title is no longer defined. Once a correlation title has been defined, it can breathe referenced in the leisure of the query instead of the table name. However, the table title can noiseless breathe referenced.

    NOTE

    Use simple, easy-to-remember correlation names. Table initials are edifying candidates for correlation names.

    Sorting Your Output

    We fill been retrieving data from one or more tables. The order of the result table has not been specified in any of the SQL statements. Therefore, the data is retrieved in an undetermined order if there is no ORDER BY clause in the SQL statement.

    NOTE

    The only guaranteed course to recur data in the required sequence is with the ORDER BY clause. Any data retrieval that is currently returned in sequence without this clause is purely based upon the data retrieval fashion at the time. A future access path change may not recur the data in the identical sequence.

    The following instance produces a list of the test candidates in alphabetical order by eventual title for the candidates who fill taken a DB2 Certification test at the TR01 test center.

    SELECT lname,initial,fname FROM db2cert.candidate c,db2cert.test_taken tt WHERE c.cid=tt.cid AND tcid='TR01' ORDER BY lname

    This instance contains a new clause, ORDER BY. After the ORDER BY clause, you can list the columns that will specify the sort order and the character of sort.

    NOTE

    Appropriate indexing may allow DB2 to avoid sorting the data to match the ORDER BY clause. If the data is already sequenced via the index, DB2 may elect to utilize the index and avoid sorting the data. DB2 cannot avoid a sort for an ORDER BY involving columns from more than one table. Where possible, include columns from only one table in the ORDER BY to give DB2 greater occasion for sort avoidance.

    The SQL can breathe modified so that the output is changed to descending order by eventual title and a secondary order column on the first title in ascending order.

    SELECT lname,fname,hphone FROM db2cert.candidate c,db2cert.test_taken tt WHERE c.cid=tt.cid AND tcid= 'TR01' ORDER BY lname DESC, fname

    In this example, the DESC keyword that follows the lname column indicates that the result table should breathe in descending order based on the eventual name. More than one record can fill the identical eventual name. This situation is quite common. There is a second column specified in the ORDER BY clause, fname. There is no keyword specifying the sort sequence based on the fname column. Therefore, the default ordering sequence (ascending) is used.

    The next instance contains three columns lname, fname, and hphone. You can reference the column that should breathe used to sort the data using the column title or by specifying its position in the select list. Using the column position is useful when the column in the select list is made up of derived columns (calculated columns) that fill no specific name.

    SELECT lname,fname,hphone FROM db2cert.candidate c,db2cert.test_taken tt WHERE c.cid=tt.cid AND tcid='TR01' ORDER BY 1 DESC, 2

    In this example, the sort order is specified using the column position. Therefore, the query result is exactly the identical as the in previous example.

    You can likewise assign an alternative column title using column renaming. The assigned title can then breathe referenced in the ORDER BY clause, and it appears as the column heading where appropriate.

    NOTE

    Although useful, coding a column position rather than a column (or renamed column) in the ORDER BY clause may lead to a different sequence if another column is inadvertently added to the query that alters the column positioning.

    The ORDER BY clause must succeed all subselects in the FULLSELECT statement. The only clauses that can succeed the ORDER BY clause are the for FOR FETCH ONLY, FOR READ ONLY, OPTIMIZE, WITH QUERYNO, FETCH FIRST n ROWS clauses.

    Derived Columns

    There are some cases when you will requisite to fulfill calculations on the data. The SQL language has some basic mathematical and string functions built in. Mathematical operations include touchstone addition, subtraction, multiplication, and division.

    The calculation can breathe defined in the WHERE clause of the SQL statement or the select list. Suppose that you requisite to figure a passing rate for a DB2 test. The passing rate is defined as the percentage of candidates that pass the test (totalpassed*100/totaltaken). The following SQL statement will accomplish this for us for test number 500:

    SELECT number, totalpassed*100/totaltaken FROM test WHERE number='500'

    In this example, the second column of the output list is a calculated column. bethink that you must exhaust the column position if you want to exhaust this calculated column for the ORDER BY clause unless you title it (as they now discuss).

    NOTE

    Occasionally, the results of a derived column may not pomp as expected. The instance using totalpassed*100/totaltaken will result in a value of 66 being retrieved. Since both the totalpassed and totaltaken columns are integers, the final result is likewise an integer, and the fractional Part is discarded. If this is not your desired result, you should exhaust other functions (like decimal) to change the course the calculation is performed or displayed.

    Naming Derived/Calculated Columns

    You can specify a column title for any expression. When you provide the derived (calculated) column with a name, the ORDER BY clause can reference the derived title to allow for a more readable SQL statement.

    The following SQL calculates the percentage of people that fill passed the DB2 Certification exams and orders the output in descending order of the passing rate.

    SELECT number,totalpassed*100/totaltaken AS PassedRate FROM test ORDER BY PassedRate DESC

    The AS clause is used to rename the default title of an element in the select list. In this example, they are giving the title of PassedRate to the result of the division of columns totalpassed by totaltaken. The named column is used in the query to specify the column that should breathe used for sorting the output.

    NOTE

    The AS keyword is optional, although it should breathe added for readability. Without the AS clause, it may breathe unclear whether the goal was to rename a column or a comma was missed between two retrieved columns.

    Functions

    In DB2, there are different types of functions provided. For example, two types of functions provided by DB2 are scalar and column functions (a third character of function called a table function is discussed in Chapter 15, "Object Relational Programming."

  • Scalar functions (also known as row functions) provide a result for each row of the result table. A scalar function can breathe used any space an expression is allowed.

  • Column functions (also known as vector functions) labor with a group of rows to provide a result. The group is specified using a FULLSELECT and optionally grouped using the GROUP BY clause.

  • In this section, they interlard you to some of the SQL functions provided with DB2. SQL functions are categorized by their implementation type. Either the functions are built in or they are extensions of DB2 and are known as user-defined functions (UDFs).

  • Built-in functions are defined within the SQL standards, and they are provided by DB2. These can breathe either scalar or column functions.

  • UDFs are not defined within the SQL standards because they are extensions of the current SQL language. These functions can breathe developed by a DB2 administrator or application developer. UDFs can breathe either scalar or table functions, but not column functions. Once the UDFs fill been created, they can breathe invoked by any discontinue user with the proper privileges. For more information about UDFs, refer to Chapter 15.

  • Scalar Functions

    Scalar functions are applied to each row of data, and there is a per-row result provided. If they want to retrieve only the first three digits of telephone numbers for each candidate, they could exhaust a scalar function. The function that is used is called SUBSTR. The arguments for this function include a string data character column, a dawn offset, and length. The output data character and impute of the function depend on the input data character and attribute. The following instance retrieves the telephone zone code for the column wphone.

    SELECT lname, SUBSTR(CHAR(wphone),1,3) FROM db2cert.candidate

    The SUBSTR function is a scalar function. In this example, SUBSTR returns a character string of three characters. The result string corresponds to the first three characters of the wphone column. This function is known as a string function because it works with any string data type. If they wanted to provide the output column with a meaningful name, they could provide an alias, as was done for calculated columns.

    In the instance above, the substring starts from the dawn of the string, because they betoken one (1) as the second parameter of the function. The length of the resulting string is indicated in the third argument. In their example, the length is three. Note that the data character of the wphone column is phone, so a casting function is used to transmute the phone data character to the char data type.

    The following query will provide the month when the exam was taken. The input for this function is a DATE string, and the output is an integer.

    SELECT fname, MONTH (date_taken) FROM candidate c, test_taken tt WHERE c.cid=tt.cid Column Functions

    Column functions provide a single result for a group of qualifying rows for a specified table or view. Many common queries can breathe satisfied using column functions where they include common tasks, such as finding the smallest value, the largest value, or the tolerable value for a group of data records. In the following instance you can obtain the maximum length of time of any of the DB2 Certification exams:

    SELECT MAX("length") FROM test

    Because the length column shares its title with the length scalar function, the column title is encased within double-quotes to distinguish this as a column and not a function.

    If they added a WHERE clause to this example, the maximum would depict the maximum length for the qualifying rows, since the predicate is used to filter the data prior to the application of the MAX function.

    This next instance calculates the tolerable of the number of seats for all of the test centers. Notice the column function AVG is used in this example:

    SELECT AVG(noseats) FROM test_center

    DB2 provides many more built-in functions. If you are interested in calculating statistical information, you can exhaust statistical functions, such as VARIANCE, STDDEV, or a sampling of these functions.

    NOTE

    MAX and MIN functions can breathe either column or scalar functions depending on the input arguments.

    Grouping Values

    Many queries require some flat of aggregated data. This is accomplished in SQL through the exhaust of the GROUP BY clause. The following SQL obtains the tolerable number of seats for each country:

    SELECT country, AVG(noseats) FROM test_center GROUP BY country

    This SQL statement obtains the tolerable number of seats per country, and the GROUP BY clause tells DB2 to group together the rows that fill the identical values in the columns indicated in the GROUP BY list. In their example, they are grouping countries into subsets. As the subsets are created, DB2 calculates the tolerable of each of those groups or subsets, in this case, by each country.

    When you combine column functions and other elements, such as column names, scalar functions, or calculated columns, you must exhaust the GROUP BY clause. In this case, you must include every element that is not a column function in the GROUP BY list. The only elements that can breathe omitted in the GROUP BY list are constant values.

    The next SQL statement obtains a list that includes the tolerable slit score and minimum test length for the DB2 Certification exams. They group this list by the character of exam, as follows:

    SELECT type, AVG(cut_score), MIN("length") FROM test GROUP BY type

    NOTE

    Appropriate indexing can allow DB2 to avoid a sort to group the data rows to match the GROUP BY clause.

    It is viable to sort the output of the previous instance using an ORDER BY clause.

    NOTE

    GROUP BY may recur data in the identical order as an ORDER BY, but this is not guaranteed and is based upon the access path. The only fashion to guarantee data sequence is with an ORDER BY.

    Restricting the exhaust of Sets of Data

    Up to now, they fill discussed how to restrict output based on row conditions. With SQL, it is likewise viable to restrict that output using column functions and the GROUP BY clause. Suppose you want a list of all the test centers that fill administered more than five DB2 Certification exams. To accomplish it easier to understand, let's first derive the number of tests that fill been taken in each test center.

    SELECT tcid, count(*) FROM test_taken GROUP BY tcid

    We exhaust the weigh column function to derive the total number of tests that fill been taken in each test center. When you exhaust an asterisk (*) with the weigh function, you are indicating that you want the number of rows in a table that meet the criteria established in the SQL statement. In this example, they are grouping by TCID because they fill a number of occurrences for all the test centers in the TEST_TAKEN table. The TEST_TAKEN table has an entry for every DB2 Certification exam that has been taken. Finally, the output is restricted to only those test centers that fill administered more than four exams.

    SELECT tcid FROM test_taken GROUP BY tcid HAVING COUNT(*) > 4

    This instance introduces the HAVING clause. The HAVING clause is equivalent to the WHERE clause for groups and column functions. The HAVING clause will restrict the result set to only the groups that meet the condition specified in it. In their example, only the test centers that fill administered more than four DB2 Certification exams will breathe displayed.

    Eliminating Duplicates

    When you execute a query, you might derive duplicate rows in the reply set. The SQL language provides a special clause to remove the duplicate rows from your output. The following SQL generates a list of names and phone numbers for all the candidates who fill taken a test. In the following example, they eradicate the duplicate rows from their output list using the distinct clause.

    SELECT distinct fname,wphone,hphone FROM candidate c,test_taken tt WHERE c.cid=tt.cid

    The distinct clause can likewise breathe used with the weigh function. When you exhaust distinct inside a weigh function, it will not weigh the duplicate entries for a particular column. The following instance allows you to weigh how many different test centers fill candidates registered.

    SELECT COUNT(DISTINCT tcid) FROM test_taken

    This instance provides the number of test centers that are registered in the TEST_TAKEN table. bethink that all the candidates who fill registered for DB2 Certification exams are stored in this table. accomplish certain that you understand the incompatibility between COUNT(*), COUNT(colname), and COUNT(DISTINCT colname). They are very similar in syntax but differ in function.

    NOTE

    COUNT(*) returns a weigh of all rows that qualify against the WHERE clause. COUNT(colname) returns a weigh of all rows that qualify against the WHERE clause, with null occurrences of colname removed. COUNT(DISTINCT colname) counts distinct occurrences of colname, with nulls removed.

    Searching for String Patterns

    SQL has a powerful predicate that allows you to search for patterns in character string columns. This is the enjoy predicate. Suppose you want to generate a list of the candidates whose first title starts with the epistle G.

    SELECT fname,lname,wphone,hphone FROM candidate WHERE fname enjoy 'G%' ORDER BY lname,fname

    In this query, they exhaust a wildcard character with the enjoy predicate. In SQL, the percent character (%) is a substitute for zero or more characters. The search string G% can breathe substituted with names enjoy George, Gary, Ginger, and so on (since the percent character can substitute zero or more characters, the search string can likewise breathe a single epistle G).

    The percent character can breathe used any space in the search string. It likewise can breathe used as many times as you requisite it. The percent sign is not case-sensitive, so it can select the space of uppercase or lowercase letters. However, the constant characters included in your search string are case-sensitive.

    Another wildcard character used with the enjoy predicate is the underline character (_). This character substitutes one and only one character. The underline character can select the space of any character. However, the underline character cannot breathe substituted for an vacuous character.

    NOTE

    If the pattern needs to search for occurrences of the wildcard characters % and _ as their actual values, then the escape clause is used to specify a character that precedes the percent or underscore in the pattern.

    The previous SQL can breathe modified to include all candidates' names and the telephone numbers for those candidates whose title has a lowercase epistle "a" as its second letter.

    SELECT fname,lname,wphone,hphone FROM candidate WHERE fname enjoy '_a%' ORDER BY lname,fname

    This instance uses two wildcard characters that labor with the enjoy predicate. The search string in this instance can include names, such as Paul, Gabriel, or Natalie. (The first character may breathe any character, the lowercase epistle "a" is the second character in the string, and the string ends with any number of characters.)

    NOTE

    When the pattern in a enjoy predicate is a fixed-length host variable, the amend length must breathe specified for the string to breathe returned. 'G%' assigned to an 8-byte variable (LIKE :variable) will search for all occurrences of 'G% ' (G, followed by any character, followed by 6 blank characters). To find rows that start with a G, then 'G%%%%%%%' should breathe assigned to the fixed-length variable.

    Searching for Data in Ranges

    SQL likewise offers us a sweep operator. This operator is used to restrict rows that are in a particular sweep of values. reckon the requirement to list those candidates whose scores in the DB2 Certification exam are between 60 and 75.

    SELECT distinct fname,lname,wphone,hphone FROM candidate c, test_taken tt WHERE c.cid=tt.cid AND score BETWEEN 60 AND 75

    The BETWEEN predicate includes the values that you specify for searching your data. An notable fact about the BETWEEN predicate is that it can labor with character ranges as well.

    In addition to the score requirement, this instance modifies the SQL to include only those candidates whose eventual title begins with a epistle between B and G.

    SELECT distinct fname,lname,wphone,hphone FROM candidate c, test_taken tt WHERE c.cid=tt.cid AND score BETWEEN 60 AND 75 AND lname BETWEEN 'B' AND 'GZ'

    In this example, the second BETWEEN predicate contains character values. They requisite to specify the GZ value to include all the viable names that start with the epistle G. This was done assuming that the epistle Z is the eventual viable value in the alphabet.

    NOTE

    The arguments of the BETWEEN clause are not interchangeable; the first must specify the low value, and the second, the towering value. BETWEEN 1 AND 2 will recur all values within the sweep (inclusive of 1 and 2). BETWEEN 2 AND 1 will recur zero rows.

    Searching for Null Values

    Null values depict an unknown value for a particular episode of an entity. They can exhaust a null value in the cases where they don't know a particular value of a column. Let's inform that they want a list of all those candidates whose score is not yet input. This condition is represented with a null value.

    SELECT fname,lname,wphone,hphone FROM candidate c, test_taken tt WHERE c.cid=tt.cid AND score IS NULL

    The IS predicate is used to search for the null value in this example. bethink that the null value means "unknown." Because it has no particular value, it can't breathe compared with other values. You can't exhaust conditional operands, such as equal (=) or greater than (>), with null values.

    Searching for Negative Conditions

    The BETWEEN, IS, and enjoy predicates always recognize for the values that meet a particular condition. These predicates can likewise breathe used to recognize for values that don't meet a particular criterion.

    The NOT predicate can breathe used to recognize for the contradictory condition, combined with the LIKE, BETWEEN, and IS predicate, to accomplish negative searches, as shown in the following example. This instance has a enjoy predicate combined with the NOT predicate. They want a list of those candidates whose eventual names Do not start with the epistle S.

    SELECT distinct fname,lname,wphone,hphone FROM candidate WHERE lname NOT enjoy 'S%' ORDER BY lname,fname

    The next instance has a BETWEEN predicate combined with the NOT predicate. They want the list of those candidates whose score, in any test, is not in the sweep 60 to 75.

    SELECT distinct fname,lname,wphone,hphone FROM candidate c, test_taken tt WHERE c.cid=tt.cid AND integer(score) NOT BETWEEN 60 and 75

    In this example, the NOT predicate will exclude all the values that are in the sweep 60 to 75.

    Negation can likewise breathe applied to the null value. This SQL produces a report that searches for those candidates that fill a seat number assigned. This is expressed with a NOT NULL value.

    SELECT distinct fname,lname,wphone,hphone FROM candidate c, test_taken tt WHERE c.cid=tt.cid AND seat_no IS NOT NULL

    NOTE

    The NOT operator can likewise breathe used to negate the touchstone comparison operators, =, <, <=, >, and >=.

    When dealing with nulls, NOT or negation may not recur the contradictory of the positive logic. For example, WHERE SEAT_NO = 1 will recur only the rows for seat number 1. Any value other than 1 is discarded, as these rows are FALSE, including nulls, since these are unknown. WHERE SEAT_NO <> 1 excludes rows where the seat number is 1, and likewise discards nulls because these are unknown.

    Searching for a Set of Values

    In SQL, it is viable to establish a restriction condition based on a set of values. Suppose that you requisite a list of the test centers that fill candidates registered for the DB2 Fundamentals test and for the DB2 Application evolution test. This can breathe queried with the following statement:

    SELECT distinct name,phone FROM test_center tc, test_taken tt WHERE tc.tcid=tt.tcid AND (number = '500' or number ='502')

    To simplify building multiple OR conditions when multiple values for the identical column are being compared, it is viable to rewrite the statement using the IN clause.

    SELECT distinct name,phone FROM test_center tc, test_taken tt WHERE tc.tcid=tt.tcid AND number IN ('500','502')

    The IN clause is used to denote a set of values. In this example, they exhaust a constant set of values.

    You can likewise exhaust the NOT predicate with the IN clause. In this case, the condition will breathe actual when a value is not present in the set of values provided to the IN clause. You can exhaust as many values as you wish in the IN clause, within the defined limits of the size of a SQL statement.

    Advanced Selection Functionality

    In Chapter 4, "Advanced SQL Coding," they will recognize at more of the functionality and power of the SELECT statement. They will cover topics such as

  • Subqueries
  • Inner and outer joins
  • Nested table expressions
  • CASE expressions
  • Row expressions
  • Unions

  • IBM pulls curtain on DB2 7.0 for mainframes | killexams.com existent questions and Pass4sure dumps

    IBM ON TUESDAY announced not only a new 64-bit version of DB2 for mainframes, but likewise new tools to back DB2 7.0 for OS/390 and IBM's zSeries.

    Armonk, N.Y.-based IBM likewise broke some of the utilities out of the core database and is shipping them as stand-alone products.

    Big Blue made four sets of utilities into stand-alone products to encourage control the cost of OS/390 software, according to Jeff Jones, senior program manager in IBM's data management group

    "The utilities fill evolved into something that can stand alone. They can compete in the market," Jones said.

    IBM divided the utilities into three distinct products: a package of operational utilities, a diagnostic and recovery package, and the more encompassing DB2 Utility Suite.

    In addition to the utilities, IBM likewise announced approximately a dozen new tools for DB2 on the mainframe. The company brought to market eventual September nearly 35 tools, and began competing with Islandia, N.Y.-based Computer Associates and BMC in Houston, which analysts list as the current market share leader.

    Framingham, Mass.-based IDC said the market for mainframe database tools is growing at 13.4 percent annually and is expected to exceed $2 billion by 2003.

    On the tools side, IBM's offerings for mainframe databases encompass administration, performance management, and applications management, as well as recovery and replication. Jones said that the new tools incrementally enhance all categories.

    "We anticipate every six months to proclaim new tools," he added.

    The new version of DB2, numbered 7.0 and slated to breathe available March 30, focuses on providing a better engine for e-business and more back for XML, such as XML extender and a text extender that is XML-aware -- features that IBM previously added to version of DB2 for Windows and Unix.

    "We establish so much accent on Unix and Windows because we're newer there, but there are a lot of architectural things, such as availability and scalability enhancements, that start on System 390," Jones said.

    Jones continued, for instance, that DB2 for OS/390 can ply nearly 1 million simultaneous users.

    And one entirely new feature in DB2 for OS/390 is Crossloader, which enables customers to build a DB2 database on OS/390 with data from other relational databases.

    Jones said that IBM plans to accomplish Crossloader available for Windows and Unix in the future.

    A new pricing schema accompanies the latest iteration of the database, dubbed Value Unit Pricing, which aims to breathe more efficient for high-end customers, Jones added.

    IBM likewise announced its 10,000th licensee of DB2 for OS/390, CommerceQuest, a Tampa, Fla.-based supplier of traffic integration software and services. Seattle-based Boeing was the first, in 1983, and its 777 aircraft was the first to breathe built on DB2 for OS/390.

    This story, "IBM pulls curtain on DB2 7.0 for mainframes " was originally published by InfoWorld.


    How to derive DB2 admin certified | killexams.com existent questions and Pass4sure dumps

    I'm interested in doing certification in DB2 administration for OS/390. I would enjoy to master the subject, not just derive the certification.

    Well, the best course to master any subject is by doing it. So, with that in mind, you should secure a position where you fill access to DB2 and requisite to labor with it to fulfill your job. But, I'm guessing that your objective is to derive a job and that you are looking to derive certified to obtain one. If that is the case, then there are some steps you can take. First of all, reckon obtaining the following books for study and reference: DB2 Developer's Guide, 5th edition by Craig S. Mullins Db2 For The Z/os Version 8 Certification by Susan Lawson DB2 Universal Database for OS/390 v7.1 Application Certification usher by Susan Lawson You should likewise download, and review, all of the DB2 for z/OS manuals from the IBM Web site. Additionally, regularly review the in-depth technical articles published by IBM at its developerWorks site. Other edifying Web sites to bookmark and review include Search390.com, SearchDatabase.com, dbazine.com, DB2 for OS390, and DB2 Times. Regarding your final question, I would inform that the best course to obtain my DBA bespeak is via amazon.com.

    Editor's note: Do you conform with this expert's response? If you fill more to share, post it in one of their .VO7aaqqaAFk.0@/search390>discussion forums.



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