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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 artery to pick up 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 pick up the certification.

neatly, the most beneficial artery to grasp any discipline is with the aid of doing it. So, with that in intellect, be confident to secure a position where you tolerate got entry to DB2 and necessity to drudgery with it to function your job. but, i'm guessing that your goal is to pick up a job and that you just want to pick up certified to attain one. if that is the case, then there are some steps that you would be 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 artery of Susan Lawson DB2 regularly occurring Database for OS/390 v7.1 utility Certification e book through Susan Lawson recollect to furthermore 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 artery 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 ultimate question, i would bellow that the most fulfilling approach to harvest my DBA ebook is by artery of amazon.com.

Editor's observe: Do you accept as true with this knowledgeable's response? in case you tolerate 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 exercise 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 information 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 exercise 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 equipment resource consumption similar to censorious processor utilization, I/O processing, reminiscence paging etc. IBM MLz can collect and shop these statistics over time, and build and teach fashions of device conduct, rating these behaviors, identify patterns now not effectively foreseen by artery of humans, multiply key efficiency indications (KPIs) and then feed the model results returned into the device to tolerate an consequence on gadget configuration changes that may enhance efficiency.

    The next step changed into to enforce this suite to anatomize 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 back personnel spends 25% or more of its time, " ... combating access route problems which occasions efficiency degradation and service tolerate an consequence on.". (See Reference 1).

    AI comes to Db2

    trust the plight of synchronous DBAs in a Db2 ambiance. In trendy IT world they must assist one or greater substantial information applications, cloud software and database services, application installing and configuration, Db2 subsystem and application performance tuning, database definition and administration, cataclysm recovery planning, and more. question tuning has been in actuality 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 be accessed and develops a list of candidate facts entry paths. These access paths can consist of indexes, table scans, a considerable number of table be portion of strategies and others. within the statistics warehouse and great data environments there are constantly further decisions purchasable. One of those is the actuality 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 obviate 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 impregnate 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 impregnate 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 exercise a graphical interface to build and maneuver 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 necessity a very profitable 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 mature personnel nearing retirement?

    take note furthermore that a great a portion of decreasing the overall can impregnate of ownership of these methods is to pick up 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 edge from performance tuning, one strategy is to automate the detection and correction of tuning considerations. here's the position computer studying and synthetic intelligence can be used to outstanding impact.

    Db2 12 for z/OS and synthetic Intelligence

    Db2 version 12 on z/OS makes exercise of the desktop learning facilities mentioned above to accumulate and hold 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 exercise the mannequin scoring statistics as enter to its access direction alternative algorithm.

    The consequence may noiseless be 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 exercise of AI utility does not require the DBA to tolerate data science skills or deep 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 furthermore be primarily crucial if you hold statistics in diverse places. as an example, many analytical queries against huge statistics require concurrent access to distinct information warehouse tables. These tables are frequently referred to as dimension tables, and they accommodate the statistics points always used to manage subsetting and aggregation. for instance, in a retail environment believe a table called StoreLocation that enumerates each rescue and its locality code. Queries against shop sales information might furthermore want to combination or summarize income by artery of area; therefore, the StoreLocation table can be used by artery of some massive facts queries. in this atmosphere it is generic to assume 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 substantial records enterprise analysts. From Db2's point of view, outright these queries are equal, and are forwarded to the Optimizer. youngsters, within the case of operational queries and warehouse queries they should absolutely be 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 drudgery for the Optimizer. happily, Db2 AI for z/OS can supply the Optimizer the tips it needs to design wise access direction decisions.

    the artery it Works

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

  • during a bind, rebind, build 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 information of project";
  • The researching project, which will furthermore be 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 hold this counsel in a model;
  • because the volume of records in each and every mannequin grows, the MLz Scoring service (which furthermore can be done on a zIIP processor) analyzes the mannequin statistics and scores the behavior;
  • all over the subsequent bind, rebind, build together or explain, the Optimizer now has access to the scoring for SQL fashions, and makes acceptable alterations to entry path selections.
  • There are furthermore a lot of consumer interfaces that provide the administrator visibility to the popularity of the collected SQL commentary performance records and mannequin scoring.


    IBM's desktop studying for zOS (MLz) providing is being used to extremely profitable 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 industry is ready to eat these ML and AI conclusions. How will you measure the charges and merits of the exercise of desktop getting to know? Which IT pilot corpse of workers tolerate to be 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 sensible your facts, its distribution, its integrity and your current and proposed access paths? this may assess where the DBAs spend 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 information 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 outright articles via Lockwood Lyon

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

    This chapter is from the book 

    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 stare 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 furthermore stare at various aspects of SQL, a necessary language to understand though the comprehension even will vary depending on the user's activity.

    This chapter is from the book 

    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 be populating (inserting) data into the database and retrieving the data using many powerful methods. Depending on the sophistication of the database users, they can exercise 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 insert more tangled methods of data manipulation. The DB2 Certification database will be 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 be added to a SELECT statement. Similarly, if the data is to be grouped, then a GROUP BY phrase must be added to the statement.

    Now, let's review the DB2CERT database design defined in the previous chapter and maneuver 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 center (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 furthermore to maintain their test scores.


    The longest SQL statement is 32,765 bytes.

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

    Retrieving the Entire Table

    The most basic of outright retrieval command involves the SELECT statement with no operators other than the title of the table. This SQL statement retrieves outright of the candidates who tolerate 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 be 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 be 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 testify that outright columns of a table are being referenced. In this example, the SQL statement refers to outright 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 accommodate the new column.


    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 outright of the column names you want to survey in the SELECT statement. They could tolerate obtained the selfsame 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;


    The * character is used to advert to outright of the columns defined for a table. The order of the columns in the result table is the selfsame 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 great it is advisable to be confident 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 illustration references a single table called DB2CERT.TEST_TAKEN. The SELECT and FROM clauses are required in outright 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 illustration 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 parade the test center 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.


    We advert to the output of a SELECT statement as the result table because the output of outright SELECT statements can be 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 be accomplished through the exercise of predicates defined in a SQL WHERE clause. To restrict the result set, they necessity to add a WHERE clause to the SQL statement.


    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 be evaluated by DB2 before the result table is returned to the halt user. There are many convincing types of predicates that can be used. In the following example, the equality (=) predicate is used to restrict the records to only those candidates who tolerate taken a DB2 Certification test at the test center TR01.

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

    The WHERE clause furthermore 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 illustration of a basic predicate. A basic predicate compares two values. In addition, more tangled predicates, such as LIKE, BETWEEN, and IN, are furthermore convincing and will be discussed later.


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

    Predicate Evaluation for UDTs

    The column TCID was defined as a user-defined data type. To design the comparison in the WHERE clause valid, a casting function needs to be 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 be compatible (same data ilk or a compatible data type). They can accomplish the data ilk 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.


    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 practicable to combine multiple conditions (predicates) in a single SQL statement. The predicates can be 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 strike the result set (known as set closure).

    The next illustration retrieves the records for the test candidates who took a test at test center TR01 and achieved a score greater than 65. The rows that satisfy the predicates are known as the qualifying rows. The following illustration 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 outright the values from one table with outright the values from another table. This operation is not used frequently because the result table can be 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.


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

    The following illustration is a Cartesian product of outright test numbers and test names from the TEST table, with outright 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 outright 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 ilk of query results in a Cartesian product.

    The result table is a representation of outright practicable 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 be 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 represent a more useful representation of the data. In the illustration below, the query represents outright 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 illustration shown above, you want to know outright 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 illustration 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 be a multiple of the number of testing centers. Usually, when multiple tables are referenced, you should involve a cross-table relationship using a table merge or unite method, as shown in the following example. They will examine table unite 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 be normalized. Following a normalization process, a number of related tables will exist. To satisfy some of the required queries, the tables must be reconstructed. The tables are reconstructed temporarily, using a table unite 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 plenary names are stored in the CANDIDATE table. To obtain the title of a candidate, the data must be retrieved from the CANDIDATE table, using a relationship or unite strategy.

    Consider an illustration that will list the names and phone numbers of candidates who were registered to assume a DB2 Certification test in 2000. To accomplish this, they necessity 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 light retrieval by ultimate name.

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

    The output of this illustration follows. Pay special attention to the values in the CID column. It will be used as the unite 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 assume 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 involve the test candidate 444, since that candidate did not tolerate a test scheduled for 2000. They necessity to unite the two result tables based on the candidate ID values. This column is known as the unite column.


    Query performance can significantly help if the unite columns are appropriately indexed.

    The following single query will satisfy 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 unite requires a predicate that includes an expression based on columns from the tables referenced in the FROM clause. This is known as a unite predicate. The FROM clause has not changed from the Cartesian product examples. The only discrepancy is in the unite predicate (test_taken.cid = candidate.cid).


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

    The table names needed to be 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 be qualified with the table name.


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

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


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

    This benevolent of unite operation shown in the above illustration is furthermore known as an inner join. An inner unite displays only the rows that are present in both of the joined tables.

    Using Correlation Names

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

    The columns can be 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.


    Correlation names can be 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 be referenced in the ease of the query instead of the table name. However, the table title can noiseless be referenced.


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

    Sorting Your Output

    We tolerate 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.


    The only guaranteed artery to revert 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 artery at the time. A future access path change may not revert the data in the selfsame sequence.

    The following illustration produces a list of the test candidates in alphabetical order by ultimate title for the candidates who tolerate 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 illustration contains a new clause, ORDER BY. After the ORDER BY clause, you can list the columns that will specify the sort order and the ilk of sort.


    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 pick 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, involve columns from only one table in the ORDER BY to give DB2 greater occasion for sort avoidance.

    The SQL can be modified so that the output is changed to descending order by ultimate 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 be in descending order based on the ultimate name. More than one record can tolerate the selfsame ultimate 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 illustration contains three columns lname, fname, and hphone. You can reference the column that should be 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 tolerate no express 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 selfsame as the in previous example.

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


    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 outright 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 necessity to accomplish calculations on the data. The SQL language has some basic mathematical and string functions built in. Mathematical operations involve standard addition, subtraction, multiplication, and division.

    The calculation can be defined in the WHERE clause of the SQL statement or the select list. Suppose that you necessity to motif 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. recollect that you must exercise the column position if you want to exercise this calculated column for the ORDER BY clause unless you title it (as they now discuss).


    Occasionally, the results of a derived column may not parade as expected. The illustration 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 furthermore an integer, and the fractional portion is discarded. If this is not your desired result, you should exercise other functions (like decimal) to change the artery 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 tolerate 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 factor 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 be used for sorting the output.


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


    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 ilk 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 be used any position an expression is allowed.

  • Column functions (also known as vector functions) drudgery 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 insert 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 be 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 be developed by a DB2 administrator or application developer. UDFs can be either scalar or table functions, but not column functions. Once the UDFs tolerate been created, they can be invoked by any halt user with the proper privileges. For more information about UDFs, advert 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 exercise a scalar function. The function that is used is called SUBSTR. The arguments for this function involve a string data ilk column, a birth offset, and length. The output data ilk and assign of the function depend on the input data ilk and attribute. The following illustration retrieves the telephone locality 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 illustration above, the substring starts from the birth of the string, because they testify 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 ilk of the wphone column is phone, so a casting function is used to transfigure the phone data ilk 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 be satisfied using column functions where they involve common tasks, such as finding the smallest value, the largest value, or the fair value for a group of data records. In the following illustration 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 represent 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 illustration calculates the fair of the number of seats for outright 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 exercise statistical functions, such as VARIANCE, STDDEV, or a sampling of these functions.


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

    Grouping Values

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

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

    This SQL statement obtains the fair number of seats per country, and the GROUP BY clause tells DB2 to group together the rows that tolerate the selfsame 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 fair 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 exercise the GROUP BY clause. In this case, you must involve every factor that is not a column function in the GROUP BY list. The only elements that can be omitted in the GROUP BY list are constant values.

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

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


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

    It is practicable to sort the output of the previous illustration using an ORDER BY clause.


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

    Restricting the exercise of Sets of Data

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

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

    We exercise the signify column function to pick up the total number of tests that tolerate been taken in each test center. When you exercise an asterisk (*) with the signify 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 tolerate a number of occurrences for outright 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 tolerate administered more than four exams.

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

    This illustration 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 tolerate administered more than four DB2 Certification exams will be displayed.

    Eliminating Duplicates

    When you execute a query, you might pick up duplicate rows in the retort 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 outright the candidates who tolerate taken a test. In the following example, they eliminate 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 furthermore be used with the signify function. When you exercise distinct inside a signify function, it will not signify the duplicate entries for a particular column. The following illustration allows you to signify how many different test centers tolerate candidates registered.

    SELECT COUNT(DISTINCT tcid) FROM test_taken

    This illustration provides the number of test centers that are registered in the TEST_TAKEN table. recollect that outright the candidates who tolerate registered for DB2 Certification exams are stored in this table. design confident that you understand the discrepancy between COUNT(*), COUNT(colname), and COUNT(DISTINCT colname). They are very similar in syntax but disagree in function.


    COUNT(*) returns a signify of outright rows that qualify against the WHERE clause. COUNT(colname) returns a signify of outright 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 fancy predicate. Suppose you want to generate a list of the candidates whose first title starts with the note G.

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

    In this query, they exercise a wildcard character with the fancy predicate. In SQL, the percent character (%) is a substitute for zero or more characters. The search string G% can be substituted with names fancy George, Gary, Ginger, and so on (since the percent character can substitute zero or more characters, the search string can furthermore be a single note G).

    The percent character can be used any position in the search string. It furthermore can be used as many times as you necessity it. The percent badge is not case-sensitive, so it can assume the position of uppercase or lowercase letters. However, the constant characters included in your search string are case-sensitive.

    Another wildcard character used with the fancy predicate is the underline character (_). This character substitutes one and only one character. The underline character can assume the position of any character. However, the underline character cannot be substituted for an bare character.


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

    The previous SQL can be modified to involve outright candidates' names and the telephone numbers for those candidates whose title has a lowercase note "a" as its second letter.

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

    This illustration uses two wildcard characters that drudgery with the fancy predicate. The search string in this illustration can involve names, such as Paul, Gabriel, or Natalie. (The first character may be any character, the lowercase note "a" is the second character in the string, and the string ends with any number of characters.)


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

    Searching for Data in Ranges

    SQL furthermore offers us a scope operator. This operator is used to restrict rows that are in a particular scope of values. admiration 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 drudgery with character ranges as well.

    In addition to the score requirement, this illustration modifies the SQL to involve only those candidates whose ultimate title begins with a note 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 necessity to specify the GZ value to involve outright the practicable names that start with the note G. This was done assuming that the note Z is the ultimate practicable value in the alphabet.


    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 revert outright values within the scope (inclusive of 1 and 2). BETWEEN 2 AND 1 will revert zero rows.

    Searching for Null Values

    Null values represent an unknown value for a particular occurrence of an entity. They can exercise a null value in the cases where they don't know a particular value of a column. Let's bellow that they want a list of outright 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. recollect that the null value means "unknown." Because it has no particular value, it can't be compared with other values. You can't exercise conditional operands, such as equal (=) or greater than (>), with null values.

    Searching for Negative Conditions

    The BETWEEN, IS, and fancy predicates always stare for the values that meet a particular condition. These predicates can furthermore be used to stare for values that don't meet a particular criterion.

    The NOT predicate can be used to stare for the contrary condition, combined with the LIKE, BETWEEN, and IS predicate, to accomplish negative searches, as shown in the following example. This illustration has a fancy predicate combined with the NOT predicate. They want a list of those candidates whose ultimate names Do not start with the note S.

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

    The next illustration 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 scope 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 outright the values that are in the scope 60 to 75.

    Negation can furthermore be applied to the null value. This SQL produces a report that searches for those candidates that tolerate 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


    The NOT operator can furthermore be used to negate the standard comparison operators, =, <, <=, >, and >=.

    When dealing with nulls, NOT or negation may not revert the contrary of the positive logic. For example, WHERE SEAT_NO = 1 will revert 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 furthermore discards nulls because these are unknown.

    Searching for a Set of Values

    In SQL, it is practicable to establish a restriction condition based on a set of values. Suppose that you necessity a list of the test centers that tolerate candidates registered for the DB2 Fundamentals test and for the DB2 Application evolution test. This can be 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 selfsame column are being compared, it is practicable 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 exercise a constant set of values.

    You can furthermore exercise the NOT predicate with the IN clause. In this case, the condition will be true when a value is not present in the set of values provided to the IN clause. You can exercise 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 stare 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 furthermore new tools to champion DB2 7.0 for OS/390 and IBM's zSeries.

    Armonk, N.Y.-based IBM furthermore 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 back control the cost of OS/390 software, according to Jeff Jones, senior program manager in IBM's data management group

    "The utilities tolerate 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 furthermore announced approximately a dozen new tools for DB2 on the mainframe. The company brought to market ultimate 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 outright categories.

    "We await every six months to promulgate new tools," he added.

    The new version of DB2, numbered 7.0 and slated to be available March 30, focuses on providing a better engine for e-business and more champion 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 build so much emphasis 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 design 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 be more effective for high-end customers, Jones added.

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

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

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

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

    Well, the best artery to master any matter is by doing it. So, with that in mind, you should secure a position where you tolerate access to DB2 and necessity to drudgery with it to accomplish your job. But, I'm guessing that your objective is to pick up a job and that you are looking to pick up certified to obtain one. If that is the case, then there are some steps you can take. First of all, admiration 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 pilot by Susan Lawson You should furthermore download, and review, outright 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 profitable Web sites to bookmark and review involve Search390.com, SearchDatabase.com, dbazine.com, DB2 for OS390, and DB2 Times. Regarding your final question, I would bellow that the best artery to obtain my DBA book is via amazon.com.

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

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