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000-611 DB2 10.1 DBA for Linux UNIX and Windows

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000-611 exam Dumps Source : DB2 10.1 DBA for Linux UNIX and Windows

Test Code : 000-611
Test title : DB2 10.1 DBA for Linux UNIX and Windows
Vendor title : IBM
: 118 true Questions

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IBM DB2 10.1 DBA for

IBM Db2 question Optimization using AI | killexams.com true Questions and Pass4sure dumps

In September 2018, IBM introduced a recent product, IBM Db2 AI for z/OS. This synthetic intelligence engine monitors statistics entry patterns from executing SQL statements, uses computing device discovering algorithms to determine upon most fulfilling patterns and passes this advice to the Db2 query optimizer for exercise by means of subsequent statements.

laptop getting to know on the IBM z Platform

In may too of 2018, IBM announced version 1.2 of its machine gaining erudition of for z/OS (MLz) product. here's a hybrid zServer and cloud software suite that ingests efficiency data, analyzes and builds models that symbolize the fitness repute of various indications, monitors them over time and provides true-time scoring capabilities.

a few elements of this product providing are aimed at assisting a community of model builders and managers. for instance:

  • It supports numerous programming languages akin to Python, Scala and R. This allows for statistics modelers and scientists to fabricate exercise of a language with which they are general;
  • A graphical consumer interface referred to as the visible mannequin Builder guides model developers without requiring totally-technical programming abilities;
  • It includes distinctive dashboards for monitoring model results and scoring functions, in addition to controlling the device configuration.
  • This machine getting to know suite become at first geared toward zServer-based analytics functions. one of the first obvious choices become zSystem efficiency monitoring and tuning. apparatus management Facility (SMF) data that are instantly generated by the working apparatus supply the raw statistics for apparatus aid consumption comparable to faultfinding processor usage, I/O processing, reminiscence paging and so on. IBM MLz can assemble and store these records over time, and build and train models of device behavior, ranking those behaviors, determine patterns no longer effortlessly foreseen by means of people, enlarge key efficiency warning signs (KPIs) and then feed the mannequin outcomes returned into the device to absorb an outcome on system configuration changes that can enrich performance.

    The next step was to implement this suite to anatomize Db2 efficiency statistics. One solution, called the IBM Db2 IT Operational Analytics (Db2 ITOA) avow template, applies the computing device studying know-how to Db2 operational data to gain an realizing of Db2 subsystem fitness. it might dynamically build baselines for key performance symptoms, supply a dashboard of these KPIs and provides operational personnel true-time insight into Db2 operations.

    while regularly occurring Db2 subsystem efficiency is a vital ingredient in ordinary utility health and performance, IBM estimates that the DBA aid corpse of workers spends 25% or greater of its time, " ... fighting access route issues which occasions efficiency degradation and service absorb an outcome on.". (See Reference 1).

    AI involves Db2

    agree with the plight of modern DBAs in a Db2 ambiance. In trendy IT world they absorb to assist one or extra immense data purposes, cloud application and database services, utility setting up and configuration, Db2 subsystem and application performance tuning, database definition and administration, catastrophe healing planning, and greater. question tuning has been in existence due to the fact the origins of the database, and DBAs are continually tasked with this as neatly.

    The coronary heart of query route analysis in Db2 is the Optimizer. It accepts SQL statements from applications, verifies authority to access the statistics, reviews the places of the objects to subsist accessed and develops an inventory of candidate information entry paths. These entry paths can involve indexes, table scans, numerous table subsist allotment of strategies and others. within the records warehouse and massive records environments there are usually further selections attainable. One of those is the existence of summary tables (now and again called materialized query tables) that involve pre-summarized or aggregated information, for that intuition enabling Db2 to reserve away from re-aggregation processing. a different option is the starjoin entry path, ordinary in the data warehouse, where the order of desk joins is changed for efficiency explanations.

    The Optimizer then studies the candidate access paths and chooses the access path, "with the bottom can charge." cost in this context means a weighted summation of resource usage including CPU, I/O, reminiscence and other substances. ultimately, the Optimizer takes the lowest impregnate access route, retailers it in reminiscence (and, optionally, in the Db2 listing) and begins access direction execution.

    massive statistics and records warehouse operations now encompass software suites that enable the industry analyst to exercise a graphical interface to build and manipulate a miniature facts mannequin of the facts they need to analyze. The applications then generate SQL statements according to the clients’ requests.

    The issue for the DBA

    so as to conclude respectable analytics for your numerous information shops you want a superb figuring out of the statistics requirements, an realizing of the analytical functions and algorithms attainable and a excessive-performance records infrastructure. regrettably, the quantity and placement of statistics sources is increasing (both in dimension and in geography), records sizes are transforming into, and purposes proceed to proliferate in number and complexity. How should soundless IT managers lead this ambiance, exceptionally with probably the most experienced and develope corpse of workers nearing retirement?

    be mindful additionally that a big allotment of reducing the plenary can impregnate of ownership of those methods is to glean Db2 purposes to dash sooner and greater efficaciously. This constantly translates into using fewer CPU cycles, doing fewer I/Os and transporting less statistics across the community. because it's often tricky to even identify which applications could benefit from performance tuning, one method is to automate the detection and correction of tuning concerns. here's the region computer discovering and synthetic intelligence will too subsist used to terrific impact.

    Db2 12 for z/OS and synthetic Intelligence

    Db2 edition 12 on z/OS makes exercise of the computing device gaining erudition of amenities mentioned above to collect and store SQL query textual content and entry route details, as well as precise efficiency-related ancient information such as CPU time used, elapsed instances and influence set sizes. This offering, described as Db2 AI for z/OS, analyzes and outlets the information in computer learning models, with the mannequin analysis consequences then being scored and made purchasable to the Db2 Optimizer. The subsequent time a scored SQL observation is encountered, the Optimizer can then exercise the mannequin scoring information as enter to its access path option algorithm.

    The outcome should subsist a reduction in CPU consumption because the Optimizer makes exercise of mannequin scoring input to select improved entry paths. This then lowers CPU prices and speeds application response instances. a significant competencies is that the exercise of AI utility does not require the DBA to absorb statistics science erudition or deep insights into question tuning methodologies. The Optimizer now chooses the premiere entry paths based mostly now not best on SQL query syntax and information distribution statistics however on modelled and scored historic performance.

    This may too subsist specifically necessary if you reserve information in assorted locations. as an example, many analytical queries in opposition t immense statistics require concurrent access to discrete statistics warehouse tables. These tables are often referred to as dimension tables, and they hold the facts features usually used to handle subsetting and aggregation. for instance, in a retail environment accept as salubrious with a table known as StoreLocation that enumerates each rescue and its location code. Queries towards reserve sales records might too want to aggregate or summarize income by using location; hence, the StoreLocation desk might subsist used by artery of some big data queries. during this atmosphere it's ordinary to heave the dimension tables and copy them always to the immense statistics application. in the IBM world this region is the IBM Db2 Analytics Accelerator (IDAA).

    Now deem about SQL queries from each operational purposes, data warehouse clients and big statistics industry analysts. From Db2's standpoint, consummate these queries are equal, and are forwarded to the Optimizer. youngsters, within the case of operational queries and warehouse queries they should soundless certainly subsist directed to entry the StoreLocation table within the warehouse. on the other hand, the query from the company analyst in opposition t huge data tables should soundless probably access the replica of the table there. This outcomes in a proliferations of erudition entry paths, and more toil for the Optimizer. fortuitously, Db2 AI for z/OS can give the Optimizer the assistance it must fabricate smart access direction choices.

    the artery it Works

    The sequence of hobbies in Db2 AI for z/OS (See Reference 2) is often perquisite here:

  • throughout a bind, rebind, prepare or clarify operation, an SQL statement is handed to the Optimizer;
  • The Optimizer chooses the facts access course; because the alternative is made, Db2 AI captures the SQL syntax, entry direction option and question efficiency facts (CPU used, etc.) and passes it to a "studying project";
  • The gaining erudition of assignment, which may too subsist achieved on a zIIP processor (a non-commonplace-intention CPU core that doesn't component into utility licensing costs), interfaces with the computer getting to know software (MLz mannequin services) to shop this information in a model;
  • as the amount of facts in each and every model grows, the MLz Scoring service (which too can subsist accomplished on a zIIP processor) analyzes the mannequin records and scores the conduct;
  • throughout the subsequent bind, rebind, prepare or clarify, the Optimizer now has access to the scoring for SQL fashions, and makes applicable alterations to access path selections.
  • There are too quite a lot of consumer interfaces that supply the administrator visibility to the popularity of the amassed SQL observation efficiency facts and mannequin scoring.

    abstract

    IBM's machine studying for zOS (MLz) providing is being used to super outcome in Db2 edition 12 to enrich the performance of analytical queries in addition to operational queries and their associated applications. This requires management consideration, as you need to investigate that your company is prepared to consume these ML and AI conclusions. How will you measure the fees and advantages of using machine discovering? Which IT hearten group of workers need to subsist tasked to reviewing the outcome of mannequin scoring, and maybe approving (or overriding) the outcomes? How will you overview and justify the assumptions that the software makes about entry direction decisions?

    In different words, how neatly conclude you know your facts, its distribution, its integrity and your latest and proposed entry paths? this will determine the region the DBAs disburse their time in aiding analytics and operational utility efficiency.

    # # #

    Reference 1

    John Campbell, IBM Db2 wonderful EngineerFrom "IBM Db2 AI for z/OS: enhance IBM Db2 application efficiency with laptop getting to know"https://www.worldofdb2.com/routine/ibm-db2-ai-for-z-os-increase-ibm-db2-utility-performance-with-ma

    Reference 2

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


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    DBAs and builders working with IBM DB2 regularly exercise IBM records Studio. Toad DBA Suite for IBM DB2 LUW complements facts Studio with advanced features that fabricate DBAs and developers a lot more productive. How can Toad DBA Suite for IBM DB2 LUW edge your company? download the tech quick to discover.

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    RapidMiner: Product Overview and perception | killexams.com true Questions and Pass4sure dumps

    download the authoritative e-book: Cloud Computing 2019: the usage of the Cloud for competitive competencies

    See the whole checklist of computing device discovering options

    final analysis

    RapidMiner may too now not absorb the identify focus of AWS or Google, nonetheless it is a comprehensive data science platform. It aids groups in exploring, mixing and cleansing statistics, designing and refining predictive models through machine discovering and managing deployments. For organizations looking for a robust, expansive ML toolset, RapidMiner bears exploring.

    RapidMiner uses a unified interface to manipulate numerous projects although a graphical drag-and-drop strategy. It offers pre-described computer getting to know libraries however too incorporates a lot of third-party libraries. This includes a whole bunch of add-ons encompassing computer studying, textual content analytics, predictive modeling, automation and manner manage.

    This produces a quick classification and regression analysis system for both supervised and unsupervised gaining erudition of. The solution too helps split and go-validation methods that enhance the accuracy of predictive models. both Gartner and Forrester rank RapidMiner as a “leader.” The dealer additionally earned a Gartner consumer’s option 2018 award.

    Product Description

    RapidMiner strategies information science and desktop gaining erudition of from a holistic viewpoint and presents a big number of apparatus to handle myriad projects. The platform helps consummate necessary open supply facts science formats and provides greater than 60 connectors to control structured, unstructured and numerous sorts of massive information.

    https://o1.qnsr.com/log/p.gif?;n=203;c=204660772;s=9478;x=7936;f=201812281334210;u=j;z=TIMESTAMP;a=20403954;e=i

    RapidMiner boasts that it presents more than 1,500 desktop getting to know and statistics prep functions, and it supports greater than forty info forms, including SAS, ARFF, Stata and by artery of URL. It helps NoSQL, MongoDB and Casandra, and its Radoop product extends information environments into the open supply Hadoop space.

    This makes it viable to generate and re-use current R and Python code, and blend and recombine current modules with recent extensions and modules. The platform too connects to foremost cloud storage functions similar to Amazon S3 and Dropbox. It writes to Qlik QVX or Tableau TDE files.

    Overview and lines person Base

    facts scientists, developers, industry analysts and citizen statistics scientists.

    Interface

    Graphical user interface.

    Scripting Languages supported

    Python, R and RapidMiner Studio

    codecs Supported

    more than 40 file varieties together with SAS, ARFF, Stata, and by means of URL. provides wizards for Microsoft surpass and access, CSV, and database connections. presents access to NoSQL databases MongoDB and Cassandra.

    Integration

    guide for consummate JDBC database connections together with Oracle, IBM DB2, Microsoft SQL Server, MySQL, Postgres, Teradata, Ingres, VectorWise, and others.

    Reporting and Visualization

    in-built visualization tools. extensive logging capabilities.

    Pricing

    $2,500 per user annually for the little version (one hundred,000 facts rows and a pair of logical processors), $5,000 per consumer yearly for the medium edition (1,000,000 records rows and 4 logical processors) and $10,000 per person yearly for unlimited entry.

    RapidMiner Overview and features at a glance:

    supplier and lines

    RapidMiner

    ML focal point

    enormously computerized ML platform pattern for businesses aiming to exercise machine getting to know commonly.

    Key features and capabilities

    presents greater than 1,500 computing device discovering and facts prep services, and it helps more than 40 files forms. Connects to Amazon S3 and Dropbox.

    user comments

    among the highest rated data science and ML options. clients picture it as effectual and “revolutionary” notwithstanding there are complaints concerning the need of GPU help. 

    Pricing and licensing

    Tiered pricing ranging from $2,500 per consumer per year to upwards of $10,000 per consumer per 12 months.


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    DB2 10.1 DBA for Linux UNIX and Windows

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    Seven Surprising Findings About DB2 | killexams.com true questions and Pass4sure dumps

    I’ve just completed IBM DB2 for Linux, Unix and Windows (LUW) coverage here on exercise The Index, Luke as preparation for an upcoming training I’m giving. This blog post describes the major differences I’ve create compared to the other databases I’m covering (Oracle, SQL Server, PostgreSQL and MySQL).

    Free & Easy

    Well, let’s kisser it: it’s IBM software. It has a pretty long history. You would probably not expect that it is light to install and configure, but in fact: it is. At least DB2 LUW Express-C 10.5 (LUW is for Linux, Unix and Windows, Express-C is the free community edition). That might subsist another surprise: there is a free community edition. It’s not open source, but it’s free as in free beer.

    No light Explain

    The first problem I stumbled upon is that DB2 has no light artery to display an execution plan. No kidding. Here is what IBM says about it:

  • Explain a statement by prefixing it with intricate scheme for

    This stores the execution scheme in a set of tables in the database (you’ll need to create these tables first). This is pretty much enjoy in Oracle.

  • Display a stored intricate scheme using db2exfmt

    This is a command line tool, not something you can descend from an SQL prompt. To dash this instrument you’ll need shell access to a DB2 installation (e.g. on the server). That means, that you cannot exercise this instrument over an regular database connection.

  • There is another command line instrument (db2expln) that combines the two steps from above. Apart from the fact that this procedure is not exactly convenient, the output you glean an ASCII art:

    Access Plan: ----------- Total Cost: 60528.3 Query Degree: 1 Rows RETURN ( 1) Cost I/O | 49534.9 ^HSJOIN ( 2) 60528.3 68095 /-----+------\ 49534.9 10000 TBSCAN TBSCAN ( 3) ( 4) 59833.6 687.72 67325 770 | | 1.00933e+06 10000 TABLE: DB2INST1 TABLE: DB2INST1 SALES EMPLOYEES Q2 Q1

    Please note that this is just an excerpt—the plenary output of db2exfmt has 400 lines. Quite a lot information that you’ll hardly ever need. Even the information that you need consummate the time (the operations) is presented in a pretty unreadable artery (IMHO). I’m particularly thankful that consummate the numbers you view above are not labeled—that’s really the icing that renders this “tool” totally useless for the occasional user.

    However, according to the IBM documentation there is another artery to display an execution plan: “Write your own queries against the intricate tables.” And that’s exactly what I did: I wrote a view called last_explained that does exactly what it’s title suggest: it shows the execution scheme of the last statement that was explained (in a non-useless formatting):

    Explain Plan ------------------------------------------------------------ ID | Operation | Rows | Cost 1 | recur | | 60528 2 | HSJOIN | 49535 of 10000 | 60528 3 | TBSCAN SALES | 49535 of 1009326 ( 4.91%) | 59833 4 | TBSCAN EMPLOYEES | 10000 of 10000 (100.00%) | 687 Predicate Information 2 - associate (Q2.SUBSIDIARY_ID = DECIMAL(Q1.SUBSIDIARY_ID, 10, 0)) associate (Q2.EMPLOYEE_ID = DECIMAL(Q1.EMPLOYEE_ID, 10, 0)) 3 - SARG ((CURRENT DATE - 6 MONTHS) < Q2.SALE_DATE) Explain scheme by Markus Winand - NO WARRANTY http://use-the-index-luke.com/s/last_explained

    I’m pretty confident many DB2 users will impart that this presentation of the execution scheme is confusing. And that’s OK. If you are used to the artery IBM presents execution plans, just stick to what you are used to. However, I’m working with consummate kinds of databases and they consummate absorb a artery to display the execution scheme similar to the one shown above—for me this format is much more useful. Further, I’ve made a useful selection of data to display: the row signify estimates and the predicate information.

    You can glean the source of the last_explained view from here or from GitHub (direct download). I’m grave about the no warranty part. Yet I’d enjoy to know about problems you absorb with the view.

    Emulating Partial Indexes is Possible

    Partial indexes are indexes not containing consummate table rows. They are useful in three cases:

  • To preserve space when the index is only useful for a very little fraction of the rows. Example: queue tables.

  • To establish a specific row order in presence of constant non-equality predicates. Example: WHERE x IN (1, 5, 9) ORDER BY y. An index enjoy the following can subsist used to avoid a sort operation:

    CREATE INDEX … ON … (y) WHERE x IN (1, 5, 9)
  • To implement unique constraints on a subset of rows (e.g. only those WHERE energetic = 'Y').

  • However, DB2 doesn’t support a where clause for indexes enjoy shown above. But DB2 has many Oracle-compatibility features, one of them is EXCLUDE NULL KEYS: “Specifies that an index entry is not created when consummate parts of the index key hold the null value.” This is actually the hard-wired behaviour in the Oracle database and it is commonly exploited to emulate partial indexes in the Oracle database.

    Generally speaking, emulating partial indexes works by mapping consummate parts of the key (all indexed columns) to NULL for rows that should not conclude up in the index. As an example, let’s emulate this partial index in the Oracle database (DB2 is next):

    CREATE INDEX messages_todo ON messages (receiver) WHERE processed = 'N'

    The solution presented in SQL Performance Explained uses a office to map the processed rows to NULL, otherwise the receiver value is passed through:

    CREATE OR REPLACE FUNCTION pi_processed(processed CHAR, receiver NUMBER) RETURN NUMBER DETERMINISTIC AS BEGIN IF processed IN ('N') THEN recur receiver; ELSE recur NULL; conclude IF; END; /

    It’s a deterministic office and can thus subsist used in an Oracle function-based index. This won’t toil with DB2, because DB2 doesn’t allow user defined-functions in index definitions. However, let’s first complete the Oracle example.

    CREATE INDEX messages_todo ON messages (pi_processed(processed, receiver));

    This index has only rows WHERE processed IN ('N')—otherwise the office returns NULL which is not set aside in the index (there is no other column that could subsist non-NULL). Voilà: a partial index in the Oracle database.

    To exercise this index, just exercise the pi_processed office in the where clause:

    SELECT message FROM messages WHERE pi_processed(processed, receiver) = ?

    This is functionally equivalent to:

    SELECT message FROM messages WHERE processed = 'N' AND receiver = ?

    So far, so ugly. If you Go for this approach, you’d better need the partial index desperately.

    To fabricate this approach toil in DB2 they need two components: (1) the EXCLUDE NULL KEYS clause (no-brainer); (2) a artery to map processed rows to NULL without using a user-defined office so it can subsist used in a DB2 index.

    Although the second one might appear to subsist hard, it is actually very simple: DB2 can conclude expression based indexing, just not on user-defined functions. The mapping they need can subsist accomplished with regular SQL expressions:

    CASE WHEN processed = 'N' THEN receiver ELSE NULL END

    This implements the very same mapping as the pi_processed office above. remember that CASE expressions are first class citizens in SQL—they can subsist used in DB2 index definitions (on LUW just since 10.5):

    CREATE INDEX messages_not_processed_pi ON messages (CASE WHEN processed = 'N' THEN receiver ELSE NULL END) EXCLUDE NULL KEYS;

    This index uses the CASE expression to map not to subsist indexed rows to NULL and the EXCLUDE NULL KEYS feature to forestall those row from being stored in the index. Voilà: a partial index in DB2 LUW 10.5.

    To exercise the index, just exercise the CASE expression in the where clause and check the execution plan:

    SELECT * FROM messages WHERE (CASE WHEN processed = 'N' THEN receiver ELSE NULL END) = ?; Explain Plan ------------------------------------------------------- ID | Operation | Rows | Cost 1 | recur | | 49686 2 | TBSCAN MESSAGES | 900 of 999999 ( .09%) | 49686 Predicate Information 2 - SARG (Q1.PROCESSED = 'N') SARG (Q1.RECEIVER = ?)

    Oh, that’s a immense disappointment: the optimizer didn’t heave the index. It does a plenary table scan instead. What’s wrong?

    If you absorb a very proximate eye at the execution scheme above, which I created with my last_explained view, you might view something suspicious.

    Look at the predicate information. What happened to the CASE expression that they used in the query? The DB2 optimizer was smart enough rewrite the expression as WHERE processed = 'N' AND receiver = ?. Isn’t that great? Absolutely!…except that this smartness has just ruined my attempt to exercise the partial index. That’s what I meant when I said that CASE expressions are first class citizens in SQL: the database has a pretty salubrious understanding what they conclude and can transform them.

    We need a artery to apply their magic NULL-mapping but they can’t exercise functions (can’t subsist indexed) nor can they exercise CASE expressions, because they are optimized away. Dead-end? Au contraire: it’s pretty light to discombobulate an optimizer. consummate you need to conclude is to obfuscate the CASE expression so that the optimizer doesn’t transform it anymore. Adding zero to a numeric column is always my first attempt in such cases:

    CASE WHEN processed = 'N' THEN receiver + 0 ELSE NULL END

    The CASE expression is essentially the same, I’ve just added zero to the RECEIVER column, which is numeric. If I exercise this expression in the index and the query, I glean this execution plan:

    ID | Operation | Rows | Cost 1 | recur | | 13071 2 | FETCH MESSAGES | 40000 of 40000 | 13071 3 | RIDSCN | 40000 of 40000 | 1665 4 | SORT (UNQIUE) | 40000 of 40000 | 1665 5 | IXSCAN MESSAGES_NOT_PROCESSED_PI | 40000 of 999999 | 1646 Predicate Information 2 - SARG ( CASE WHEN (Q1.PROCESSED = 'N') THEN (Q1.RECEIVER + 0) ELSE NULL conclude = ?) 5 - START ( CASE WHEN (Q1.PROCESSED = 'N') THEN (Q1.RECEIVER + 0) ELSE NULL conclude = ?) quit ( CASE WHEN (Q1.PROCESSED = 'N') THEN (Q1.RECEIVER + 0) ELSE NULL conclude = ?)

    The partial index is used as intended. The CASE expression appears unchanged in the predicate information section.

    I haven’t checked any other ways to emulate partial indexes in DB2 (e.g., using partitions enjoy in more recent Oracle versions).

    As always: just because you can conclude something doesn’t signify you should. This approach is so ugly—even more repugnant than the Oracle workaround—that you must desperately need a partial index to justify this maintenance nightmare. Further it will quit working whenever the optimizer becomes smart enough to optimize +0 away. However, then you just need set aside an even more repugnant obfuscation in there.

    INCLUDE Clause Only for Unique Indexes

    With the involve clause you can add extra columns to an index for the sole purpose to allow in index-only scan when these columns are selected. I knew the involve clause before because SQL Server offers it too, but there are some differences:

  • In SQL Server involve columns are only added to the leaf nodes of the index—not in the root and branch nodes. This limits the impact on the B-tree’s depth when adding many or long columns to an index. This too allows to bypass some limitations (number of columns, total index row length, allowed data types). That doesn’t appear to subsist the case in DB2.

  • In DB2 the involve clause is only telling for unique indexes. It allows you to invoke the uniqueness of the key columns only—the involve columns are just not considered when checking for uniqueness. This is the same in SQL Server except that SQL Server supports involve columns on non-unique indexes too (to leverage the above-mentioned benefits).

  • Almost No NULLS FIRST/LAST Support

    The NULLS FIRST and NULLS last modifiers to the order by clause allow you to specify whether NULL values are considered as larger or smaller than non-NULL values during sorting. Strictly speaking, you must always specify the desired order when sorting nullable columns because the SQL yardstick doesn’t specify a default. As you can view in the following chart, the default order of NULL is indeed different across various databases:

    Figure A.1. Database/Feature Matrix

    In this chart, you can too view that DB2 doesn’t support NULLS FIRST or NULLS LAST—neither in the order by clause no in the index definition. However, note that this is a simplified statement. In fact, DB2 accepts NULLS FIRST and NULLS last when it is in line with the default NULLS order. In other words, ORDER BY col ASC NULLS FIRST is valid, but it doesn’t change the result—NULLS FIRST is anyways the default. same is salubrious for ORDER BY col DESC NULLS LAST—accepted, but doesn’t change anything. The other two combinations are not telling at consummate and succumb a syntax error.

    SQL:2008 FETCH FIRST but not OFFSET

    DB2 supports the fetch first … rows only clause for a while now—kind-of impressive considering it was “just” added with the SQL:2008 standard. However, DB2 doesn’t support the offset clause, which was introduced with the very same release of the SQL standard. Although it might eye enjoy an capricious omission, it is in fact a very sensible scoot that I deeply respect. offset is the root of so much evil. In the next section, I’ll intricate how to live without offset.

    Side node: If you absorb code using offset that you cannot change, you can soundless activate the MySQL compatibility vector that makes confine and offset available in DB2. laughable enough, combining fetch first with offset is then soundless not viable (that would subsist yardstick compliant).

    Decent Row-Value Predicates Support

    SQL row-values are multiple scalar values grouped together by braces to form a sole logical value. IN-lists are a common use-case:

    WHERE (col_a, col_b) IN (SELECT col_a, col_b FROM…)

    This is supported by pretty much every database. However, there is a second, hardly known use-case that has pretty impecunious support in today’s SQL databases: key-set pagination or offset-less pagination. Keyset pagination uses a where clause that basically says “I’ve seen everything up till here, just give me the next rows”. In the simplest case it looks enjoy this:

    SELECT … FROM … WHERE time_stamp < ? ORDER BY time_stamp DESC FETCH FIRST 10 ROWS ONLY

    Imagine you’ve already fetched a bunch of rows and need to glean the next few ones. For that you’d exercise the time_stamp value of the last entry you’ve got for the bind value (?). The query then just recur the rows from there on. But what if there are two rows with the very same time_stamp value? Then you need a tiebreaker: a second column—preferably a unique column—in the order by and where clauses that unambiguously marks the region till where you absorb the result. This is where row-value predicates arrive in:

    SELECT … FROM … WHERE (time_stamp, id) < (?, ?) ORDER BY time_stamp DESC, id DESC FETCH FIRST 10 ROWS ONLY

    The order by clause is extended to fabricate confident there is a well-defined order if there are equal time_stamp values. The where clause just selects what’s after the row specified by the time_stamp and id pair. It couldn’t subsist any simpler to express this selection criteria. Unfortunately, neither the Oracle database nor SQLite or SQL Server understand this syntax—even though it’s in the SQL yardstick since 1992! However, it is viable to apply the same logic without row-value predicates—but that’s rather inconvenient and light to glean wrong.

    Even if a database understands the row-value predicate, it’s not necessarily understanding these predicates salubrious enough to fabricate proper exercise of indexes that support the order by clause. This is where MySQL fails—although it applies the logic correctly and delivers the perquisite result, it does not exercise an index for that and is thus rather slow. In the end, DB2 LUW (since 10.1) and PostgreSQL (since 8.4) are the only two databases that support row-value predicates in the artery it should be.

    The fact that DB2 LUW has everything you need for convenient keyset pagination is too the intuition why there is absolutely no intuition to complain about the missing offset functionality. In fact I contemplate that offset should not absorb been added to the SQL yardstick and I’m delighted to view a vendor that resisted the prod to add it because its became allotment of the standard. Sometimes the yardstick is wrong—just sometimes, not very often ;) I can’t change the standard—all I can conclude is teaching how to conclude it perquisite and start campaigns enjoy #NoOffset.

    Figure A.2. Database/Feature Matrix

    If you enjoy my artery of explaining things, you’ll savor my reserve “SQL Performance Explained”.


    Don't overlook Amanda for your storage data protection needs | killexams.com true questions and Pass4sure dumps

    Chances are, you absorb never heard of Amanda… in the sense of open source that is. And if you absorb not heard of Amanda, then chances are you absorb not heard of Zmanda either. I will intricate both, and I will give you my view of why it is necessary for you to at least subsist sensible of these products and their relation to data protection. Whether you should invest in either depends on many factors that will become pellucid shortly.

    Let's start with Amanda. Amanda is the most current open source data protection product in the market today, at least based on the number of free downloads: 250,000 or more. enjoy most free downloads, these usually arrive from universities -- both students and IT folks -- and scientific labs. But, they too involve individuals from corporations that are experimenting with open source. In a nutshell, Amanda is a client/server data protection software that runs on a Linux server (backup server) and protects clients that dash Windows, Linux or Unix (only a few variants at the moment). It was developed originally at the University of Maryland and then dropped into the world of open source. Since it was distributed to the open source community, hundreds of programmers absorb contributed to its development, bug fixes and its universal dependence and feeding. As a result, the usage of the product has continued to climb dramatically over the past few years.

    You can exercise Amanda for free. You can modify it and set aside it back in the ether for free. But, enjoy consummate open source software, if the software just stopped running in the middle of the night because your client application server was not yet supported, salubrious luck trying to glean support. Or anything else. Your best stake would subsist to region your request on one of many Web sites where users and developers hearten each other out.

    But, unlike Linux operating systems (where there are companies enjoy RedHat and SUSE, which is now Novell) or Linux-based databases (where there are companies enjoy mySQL), Amanda did not absorb a "for profit" sponsor until recently. In late 2005, a newly-formed company was charged with working to fabricate Amanda a more usable product that would subsist able to support enterprises of consummate sizes. In keeping with the open source model, Zmanda has grabbed leadership of this space and is feverishly encouraging additional programmers -- some internal to the company, but most belonging to other companies/organizations -- to enhance Amanda so it can effectively compete with Symantec NetBackup, EMC Networker, CommVault Galaxy, Tivoli and others that descend in the enterprise-class data protection software category. Even within the last six months, Amanda has arrive a long way. But, it too has a long artery to Go before I would deem it a plenary member of this class. Should you therefore ignore it? No. However, the intuition I am writing this column is to fabricate you sensible that, under the perquisite set of circumstances, Amanda is worth considering.

    Enter Zmanda. The company has released a specific version of Amanda (two versions, actually) that they support under the classic open source subscription model. You pay only for subscription and support and not for the product itself, just enjoy any other open source product. Of course, the whole blueprint is to cost it such that the total cost of ownership is significantly (as in one-half to one-fourth the cost) lower than other commercial products.

    But before you jump into the fray, quiz yourself the following questions:

  • Does the current product absorb support for my systems?
  • Does it absorb the features I need?
  • Does the product absorb support for my applications (e.g., Oracle, SQLserver, and DB2?)
  • Does it absorb adequate disk support?
  • What about archiving?
  • I am confident that as you eye into these options you will absorb other questions that are specific to your organization's needs. Version 2.50 of Zmanda does absorb support for Windows and Linux, but not for consummate current flavors of Unix. It should support databases and other applications in the future but does not perquisite now. It too lacks a GUI and does not yet support consummate the recent innovations that they absorb seen in the world of disk support (like VTL and CDP). But, it does absorb disk support. It too has some features that I wish they had in the other commercial offerings, enjoy a non-proprietary data format and enjoy having the faculty to conclude a recovery without requiring the vendor's software. Of course, its Linux support is excellent.

    In my view, true innovation occurs when there is a monetary incentive and there is a discontinuity in the technology curve. That is why they absorb seen the massive transformation in data protection software in the past five years. SATA was the technology that opened up opportunities that just were not available before. But, before that, one could fabricate a pretty reasonable controversy that data protection software from consummate the major vendors had become pretty bloated, and the rate of innovation was very slow. Adding support for a recent tape library does not signify as innovation in my book. It is precisely at such times, when differentiation between vendors' products is low, that open source starts to fabricate a lot of sense. Thousands of programmers start developing and creating a simpler, less cumbersome product with adequate functionality for many companies that don't need it all. Also, they are cost-sensitive and enjoy the freedom.

    That is how mySQL and, of course, Linux itself got going. Now it is Zmanda. But unlike the other segments, data protection is now experiencing phenomenal innovation. So, Amanda's (and therefore, Zmanda's) challenge will subsist to not only create the obsolete tape-based functionality but too to add consummate the recent juicy disk-based functionality that is coming in waves currently. I suspect it is up for the challenge but at least subsist sensible that there could subsist a lag before you view consummate of these features.

    It was bound to happen. If database, J2EE, server virtualization and security tools got an open source counterpart, how far behind could data protection be? If you absorb simpler needs, cost is a major issue and you crave that liberty from the immense vendor -- for whatever intuition -- then you should check out this recent space. But my advice: conclude not dash a production environment without the support that comes with Zmanda. Amanda may subsist free, but she can subsist peril without the support.

    About the author: Arun Taneja is the founder and consulting analyst for the Taneja Group. Taneja writes columns and answers questions about data management and related topics.


    IT Skills Poised To Pay | killexams.com true questions and Pass4sure dumps

    In-Depth

    IT Skills Poised To Pay

    Advances in mobility, cloud, immense Data, DevOps and digital delivery, plus the shift to more rapid release cycles of software and services, are enabling businesses to become more agile. IT workforce research and analyst hard Foote Partners assesses the IT skills gap these trends are creating, their impact on salaries and where the claim for expertise is headed.

  • By David Foote
  • 12/05/2016
  • It's difficult to find an employer not struggling to arrive up with a unique tech staffing model that balances three things: the urgencies of recent digital innovation strategies, combating ever deepening security threats, and keeping integrated systems and networks running smoothly and efficiently. The staffing challenge has moved well beyond simply having to select between contingent workers, full-time tech professionals, and a variety of cloud computing and managed services options (Infrastructure as a Service [IaaS], Platform as a Service [PaaS], Software as a Server [SaaS]). Over the next few years, managers will continue to subsist tasked with leading a massive transformation of the technology and tech-business hybrid workforce to focus on quickly and predictably delivering a wide variety of operational and revenue-generating infrastructure solutions involving Internet of Things (IoT) products and services, immense Data advanced analytics, cybersecurity, and recent mobile and cloud computing capabilities. Consequently, tech professionals and developers must align their skills and interests accordingly to hearten their employers meet existing and forthcoming digital transformation imperatives that are forcing deep, accelerated changes in technology organizations.

    As cloud infrastructure becomes more capable of economically delivering performance and data at capacities and speeds once never imagined, organizations of consummate sizes are seeking tech professionals and developers with the proper skills, knowledge, and competencies to create more agile and responsive environments.

    At the same time, they're grappling to ensure reliability of existing infrastructure where any amount of downtime is less acceptable than ever. Along with that is an onslaught of cybersecurity attacks occurring more frequently that absorb many IT managers epigram they can't find adequate labor to hearten them protect their existing networks and endpoints. The latest reminder was in the spotlight following the most powerful denial of service (DoS) beset to date in late October resulting from unprotected endpoints on surveillance cameras. IoT, machine-to-machine communications and telematics absorb introduced recent complexities ranging from the need to better secure the devices and the delivery points to which they connect. Meanwhile, the growing IoT landscape is unleashing an exponential flood of recent data from hundreds of millions of devices, and organizations need to blend their IT and operational systems and find people with immense Data analytics skills to handle the cloud-based machine learning infrastructure that's now emerging. This generational shift in IT will set aside a premium on, or create a baseline requirement for, IT professionals willing to ensue the money and view where their skills will subsist most applicable. Whether you're a manager looking to ensure your staff can deliver on these changes or an IT professional deciding on a career direction, workforce requirements and customer expectations are changing.

    If you're in the latter camp, it's necessary to understand that the supply-and-demand aspect that drives compensation is too a poignant target. IT pay has a long history of volatility and in 2016 they absorb seen even sharper swings in those premiums. Based on hiring patterns, the following overriding trends will drive market claim for IT professionals who absorb the experience, drive and skills to deliver solutions:

  • Cybersecurity: The need to protect traditional infrastructure from pervasive and ongoing attacks from a growing number of vectors and sophistication. Evidence suggests pay premiums for cybersecurity will continue to subsist stout for the coming years as the threat landscape continues to become more knotty and confounding. The elimination of traditional boundaries brought about by cloud computing and mobility and a massive recent influx of data generated by IoT devices will only exacerbate this need. More than 25 percent of identified attacks will involve IoT, according to Gartner Inc.
  • Cloud: IT infrastructure over time is transitioning to an all-cloud model, whether provided by a services provider, in the datacenter or a hybrid blend of the two. The scoot to these elastic infrastructures and op-ex approach to IT is too enabling high-performance computing and storage capacity that's ushering in the faculty to effect workloads and software-defined automation not viable with traditional client server or Web application tier infra­structures. Likewise, the scoot to cloud service-based apps such as Salesforce, Office 365 and Workday, to title just a few, is shifting the need for those with skills in edifice and managing traditional packaged software to those proficient in these recent SaaS-based solutions. The amount spent on cloud this year was forecast at $111 billion, according to Gartner. By 2020, that spending is expected to climb to $216 billion.
  • Big Data Analytics/Machine Learning: The scoot toward digital transformation is consummate about empowering users to fabricate quick decisions based on an overwhelmingly massive groundswell of data to subsist curated from recent sources such as IoT endpoints using the cloud infrastructure and enabling predictive analytics utilizing the machine learning conversational computing frameworks that Amazon Web Services Inc. (AWS), Google Inc., IBM Corp. and Microsoft are developing.
  • DevOps: The drive to bring together IT operations and progress is taking hold as the scoot to digital transformation, or at least the scheme to conclude so, means organizations must subsist more agile. A more rapid release cadence in software delivery -- from Windows and Office to open source environments and vertical applications -- requires that IT shops can build, deliver and manage systems with these dynamics. Likewise, recent programming environments and frameworks such as containers and micro-services are enabling recent classes of cloud-native applications designed for recent classes of devices and quick-witted and modern infrastructure.
  • Digital industry Transformation: This is the conclude goal of many organizations that fear, rightfully so, their industry models are at risk unless they can become digital businesses. This is the culmination of the four areas just celebrated but too includes the faculty to leverage advances in UX and UI design and the faculty to lever­age IT to hearten companies build recent products, services and support that's tuned to the digital era.
  • Selected DevOps Skills & Certifications: Pay Premiums Performance DevOps Area Tool Median Pay Premium Noncertified Skills Build and packaging tools Apache Maven 11% Build and packaging tools Ant 10% Cloud computing AWS 11% Cloud computing OpenStack 11% Configuration management Puppet 9% Configuration management Chef 9% Configuration management Ansible 9% Configuration management Salt 9% Continuous integration tools Jenkins 11% Database Couchbase Server 13% Database CouchDB 12% Debugging Go language (Golang) 13% Debugging Node.js 8% Hosting environments AWS cloud tools and solutions  11% Methodology Agile software development 10% Open source databases MySQL 9% Open source databases PostgreSQL 11% Open source databases Redis 12% SCM tools Git/GitHub 9% Scripting languages Ruby on Rails/Ruby 12% Scripting languages Python 9% Virtualization Vagrant 8% Certifications Cloud computing AWS Certified DevOps Engineer - Professional 11% Cloud computing AWS Certified Solutions Architect - Associate (Cloud)      8% Cloud computing AWS Certified Solutions Architect - Professional (Cloud)     12% Cloud computing AWS Certified SysOpsAdministrator - Associate (Cloud) 8% Configuration management Red Hat Certified Architect - DevOps 8%


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