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

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

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IBM DB2 10.1 DBA for

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

In September 2018, IBM introduced a original 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 settle upon most fulfilling patterns and passes this advice to the Db2 query optimizer for utilize by means of subsequent statements.

laptop getting to know on the IBM z Platform

In may moreover of 2018, IBM announced version 1.2 of its machine gaining scholarship 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 create utilize 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. materiel management Facility (SMF) data that are instantly generated by the working materiel supply the raw statistics for materiel 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, expand key efficiency warning signs (KPIs) and then feed the mannequin outcomes returned into the device to occupy an effect 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) acknowledge 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 classic utility health and performance, IBM estimates that the DBA aid carcass of workers spends 25% or greater of its time, " ... fighting access route issues which occasions efficiency degradation and service occupy an effect on.". (See Reference 1).

    AI involves Db2

    agree with the plight of modern DBAs in a Db2 ambiance. In trendy IT world they occupy to assist one or extra commodious 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 being 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 exist accessed and develops an inventory of candidate information entry paths. These entry paths can comprehend indexes, table scans, numerous table exist participate of strategies and others. within the records warehouse and massive records environments there are usually further selections attainable. One of those is the being of summary tables (now and again called materialized query tables) that comprehend pre-summarized or aggregated information, for that understanding enabling Db2 to preserve away from re-aggregation processing. a different option is the starjoin entry path, classic 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, memory and other substances. ultimately, the Optimizer takes the lowest freight access route, retailers it in memory (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 utilize a graphical interface to build and manipulate a miniature facts mannequin of the facts they necessity to analyze. The applications then generate SQL statements according to the clients’ requests.

    The issue for the DBA

    so as to execute 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 still IT managers guide this ambiance, exceptionally with probably the most experienced and age carcass of workers nearing retirement?

    be mindful additionally that a big participate of reducing the replete can freight of ownership of those methods is to salvage Db2 purposes to race 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 profit from performance tuning, one method is to automate the detection and correction of tuning concerns. here's the Place computer discovering and synthetic intelligence will moreover exist used to terrific impact.

    Db2 12 for z/OS and synthetic Intelligence

    Db2 edition 12 on z/OS makes utilize of the computing device gaining scholarship 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 utilize the mannequin scoring information as enter to its access path option algorithm.

    The effect should exist a reduction in CPU consumption because the Optimizer makes utilize 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 utilize of AI utility does not require the DBA to occupy statistics science scholarship or abysmal 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 moreover exist specifically significant if you preserve information in assorted locations. as an example, many analytical queries in opposition t commodious statistics require concurrent access to several 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 correct with a table known as StoreLocation that enumerates each save and its location code. Queries towards preserve sales records might moreover want to aggregate or summarize income by using location; hence, the StoreLocation desk might exist used by pass of some big data queries. during this atmosphere it's classic to recall the dimension tables and copy them always to the commodious statistics application. in the IBM world this region is the IBM Db2 Analytics Accelerator (IDAA).

    Now reckon about SQL queries from each operational purposes, data warehouse clients and big statistics industry analysts. From Db2's standpoint, any these queries are equal, and are forwarded to the Optimizer. youngsters, within the case of operational queries and warehouse queries they should still certainly exist 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 still probably access the replica of the table there. This outcomes in a proliferations of scholarship entry paths, and more travail for the Optimizer. fortuitously, Db2 AI for z/OS can give the Optimizer the assistance it must create smart access direction choices.

    the pass it Works

    The sequence of hobbies in Db2 AI for z/OS (See Reference 2) is often birthright 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 scholarship of assignment, which may moreover exist 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 moreover can exist 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 moreover 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 effect 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 necessity 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 attend group of workers necessity to exist tasked to reviewing the outcome of mannequin scoring, and maybe approving (or overriding) the outcomes? How will you overview and warrant the assumptions that the software makes about entry direction decisions?

    In different words, how neatly execute you know your facts, its distribution, its integrity and your latest and proposed entry paths? this will determine the Place the DBAs expend 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


    How Toad DBA Suite for IBM DB2 LUW complements facts Studio | killexams.com real Questions and Pass4sure dumps

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

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

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

    See the entire checklist of computing device discovering options

    final analysis

    RapidMiner may moreover now not occupy 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 moreover incorporates a lot of third-party libraries. This includes a entire 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 scholarship of. The solution moreover 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 scholarship of from a holistic viewpoint and presents a big number of materiel to handle myriad projects. The platform helps any significant 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 pass of URL. It helps NoSQL, MongoDB and Casandra, and its Radoop product extends information environments into the open supply Hadoop space.

    This makes it feasible to generate and re-use current R and Python code, and coalesce and recombine current modules with original extensions and modules. The platform moreover 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 national 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 outdo and access, CSV, and database connections. presents access to NoSQL databases MongoDB and Cassandra.

    Integration

    guide for any 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 tiny 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 exemplar for businesses aiming to utilize 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 represent it as efficient and “revolutionary” notwithstanding there are complaints concerning the lack 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 real questions and Pass4sure dumps

    I’ve just completed IBM DB2 for Linux, Unix and Windows (LUW) coverage here on utilize The Index, Luke as preparation for an upcoming training I’m giving. This blog post describes the major differences I’ve found 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 anticipate that it is facile 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 exist another surprise: there is a free community edition. It’s not open source, but it’s free as in free beer.

    No facile Explain

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

  • Explain a statement by prefixing it with define method for

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

  • Display a stored define method using db2exfmt

    This is a command line tool, not something you can Fall from an SQL prompt. To race this instrument you’ll necessity shell access to a DB2 installation (e.g. on the server). That means, that you cannot utilize 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 salvage 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 replete output of db2exfmt has 400 lines. Quite a lot information that you’ll hardly ever need. Even the information that you necessity any the time (the operations) is presented in a pretty unreadable pass (IMHO). I’m particularly thankful that any the numbers you espy 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 pass to array an execution plan: “Write your own queries against the define tables.” And that’s exactly what I did: I wrote a view called last_explained that does exactly what it’s name suggest: it shows the execution method of the eventual statement that was explained (in a non-useless formatting):

    Explain Plan ------------------------------------------------------------ ID | Operation | Rows | Cost 1 | revert | | 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 - relate (Q2.SUBSIDIARY_ID = DECIMAL(Q1.SUBSIDIARY_ID, 10, 0)) relate (Q2.EMPLOYEE_ID = DECIMAL(Q1.EMPLOYEE_ID, 10, 0)) 3 - SARG ((CURRENT DATE - 6 MONTHS) < Q2.SALE_DATE) Explain method by Markus Winand - NO WARRANTY http://use-the-index-luke.com/s/last_explained

    I’m pretty positive many DB2 users will shriek that this presentation of the execution method is confusing. And that’s OK. If you are used to the pass IBM presents execution plans, just stick to what you are used to. However, I’m working with any kinds of databases and they any occupy a pass to array the execution method 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 weigh estimates and the predicate information.

    You can salvage the source of the last_explained view from here or from GitHub (direct download). I’m staid about the no warranty part. Yet I’d dote to know about problems you occupy with the view.

    Emulating Partial Indexes is Possible

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

  • To preserve space when the index is only useful for a very tiny 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 dote the following can exist 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 active = 'Y').

  • However, DB2 doesn’t champion a where clause for indexes dote 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 any 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 any parts of the key (all indexed columns) to NULL for rows that should not cessation 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 revert receiver; ELSE revert NULL; cessation IF; END; /

    It’s a deterministic office and can thus exist used in an Oracle function-based index. This won’t travail 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 achieve in the index (there is no other column that could exist non-NULL). Voilà: a partial index in the Oracle database.

    To utilize this index, just utilize 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 recede for this approach, you’d better necessity the partial index desperately.

    To create this approach travail in DB2 they necessity two components: (1) the EXCLUDE NULL KEYS clause (no-brainer); (2) a pass to map processed rows to NULL without using a user-defined office so it can exist used in a DB2 index.

    Although the second one might seem to exist hard, it is actually very simple: DB2 can execute expression based indexing, just not on user-defined functions. The mapping they necessity can exist 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. recall that CASE expressions are first class citizens in SQL—they can exist 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 exist 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 utilize the index, just utilize 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 | revert | | 49686 2 | TBSCAN MESSAGES | 900 of 999999 ( .09%) | 49686 Predicate Information 2 - SARG (Q1.PROCESSED = 'N') SARG (Q1.RECEIVER = ?)

    Oh, that’s a commodious disappointment: the optimizer didn’t recall the index. It does a replete table scan instead. What’s wrong?

    If you occupy a very near notice at the execution method above, which I created with my last_explained view, you might espy 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 utilize 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 expedient understanding what they execute and can transform them.

    We necessity a pass to apply their magic NULL-mapping but they can’t utilize functions (can’t exist indexed) nor can they utilize CASE expressions, because they are optimized away. Dead-end? Au contraire: it’s pretty facile to discombobulate an optimizer. any you necessity to execute 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 utilize this expression in the index and the query, I salvage this execution plan:

    ID | Operation | Rows | Cost 1 | revert | | 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 cessation = ?) 5 - START ( CASE WHEN (Q1.PROCESSED = 'N') THEN (Q1.RECEIVER + 0) ELSE NULL cessation = ?) quit ( CASE WHEN (Q1.PROCESSED = 'N') THEN (Q1.RECEIVER + 0) ELSE NULL cessation = ?)

    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 dote in more recent Oracle versions).

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

    INCLUDE Clause Only for Unique Indexes

    With the comprehend 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 comprehend clause before because SQL Server offers it too, but there are some differences:

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

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

  • Almost No NULLS FIRST/LAST Support

    The NULLS FIRST and NULLS eventual 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 touchstone doesn’t specify a default. As you can espy 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 moreover espy that DB2 doesn’t champion 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 eventual 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 correct for ORDER BY col DESC NULLS LAST—accepted, but doesn’t change anything. The other two combinations are not telling at any and defer 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 champion the offset clause, which was introduced with the very same release of the SQL standard. Although it might notice dote an whimsical omission, it is in fact a very prudent scamper that I deeply respect. offset is the root of so much evil. In the next section, I’ll define how to live without offset.

    Side node: If you occupy code using offset that you cannot change, you can still activate the MySQL compatibility vector that makes limit and offset available in DB2. droll enough, combining fetch first with offset is then still not feasible (that would exist touchstone compliant).

    Decent Row-Value Predicates Support

    SQL row-values are multiple scalar values grouped together by braces to figure a separate 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 needy champion 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 dote 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 necessity to salvage the next few ones. For that you’d utilize the time_stamp value of the eventual entry you’ve got for the bind value (?). The query then just revert the rows from there on. But what if there are two rows with the very same time_stamp value? Then you necessity a tiebreaker: a second column—preferably a unique column—in the order by and where clauses that unambiguously marks the Place till where you occupy the result. This is where row-value predicates attain 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 create positive 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 exist 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 touchstone since 1992! However, it is feasible to apply the same logic without row-value predicates—but that’s rather inconvenient and facile to salvage wrong.

    Even if a database understands the row-value predicate, it’s not necessarily understanding these predicates expedient enough to create proper utilize of indexes that champion the order by clause. This is where MySQL fails—although it applies the logic correctly and delivers the birthright result, it does not utilize 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 champion row-value predicates in the pass it should be.

    The fact that DB2 LUW has everything you necessity for convenient keyset pagination is moreover the understanding why there is absolutely no understanding to complain about the missing offset functionality. In fact I mediate that offset should not occupy been added to the SQL touchstone and I’m satisfied to espy a vendor that resisted the prick to add it because its became participate of the standard. Sometimes the touchstone is wrong—just sometimes, not very often ;) I can’t change the standard—all I can execute is teaching how to execute it birthright and start campaigns dote #NoOffset.

    Figure A.2. Database/Feature Matrix

    If you dote my pass of explaining things, you’ll esteem my engage “SQL Performance Explained”.


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

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

    Let's start with Amanda. Amanda is the most Popular open source data protection product in the market today, at least based on the number of free downloads: 250,000 or more. dote most free downloads, these usually attain from universities -- both students and IT folks -- and scientific labs. But, they moreover comprehend 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 race 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 occupy contributed to its development, bug fixes and its generic supervision and feeding. As a result, the usage of the product has continued to climb dramatically over the past few years.

    You can utilize Amanda for free. You can modify it and achieve it back in the ether for free. But, dote any open source software, if the software just stopped running in the middle of the night because your client application server was not yet supported, expedient luck trying to salvage support. Or anything else. Your best stake would exist to Place your request on one of many Web sites where users and developers attend each other out.

    But, unlike Linux operating systems (where there are companies dote RedHat and SUSE, which is now Novell) or Linux-based databases (where there are companies dote mySQL), Amanda did not occupy a "for profit" sponsor until recently. In late 2005, a newly-formed company was charged with working to create Amanda a more usable product that would exist able to champion enterprises of any 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 Fall in the enterprise-class data protection software category. Even within the eventual six months, Amanda has attain a long way. But, it moreover has a long pass to recede before I would reckon it a replete member of this class. Should you therefore ignore it? No. However, the understanding I am writing this column is to create you cognizant that, under the birthright set of circumstances, Amanda is worth considering.

    Enter Zmanda. The company has released a specific version of Amanda (two versions, actually) that they champion under the classic open source subscription model. You pay only for subscription and champion and not for the product itself, just dote any other open source product. Of course, the entire scheme is to expense 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, question yourself the following questions:

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

    In my view, real innovation occurs when there is a monetary incentive and there is a discontinuity in the technology curve. That is why they occupy 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 create a pretty reasonable dispute that data protection software from any the major vendors had become pretty bloated, and the rate of innovation was very slow. Adding champion for a original tape library does not weigh as innovation in my book. It is precisely at such times, when differentiation between vendors' products is low, that open source starts to create 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 necessity it all. Also, they are cost-sensitive and dote 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 exist to not only create the obsolete tape-based functionality but moreover to add any the original juicy disk-based functionality that is coming in waves currently. I suspect it is up for the challenge but at least exist cognizant that there could exist a lag before you espy any 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 occupy simpler needs, cost is a major issue and you crave that liberty from the commodious vendor -- for whatever understanding -- then you should check out this original space. But my advice: execute not race a production environment without the champion that comes with Zmanda. Amanda may exist free, but she can exist catastrophe 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 real questions and Pass4sure dumps

    In-Depth

    IT Skills Poised To Pay

    Advances in mobility, cloud, commodious 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 firm Foote Partners assesses the IT skills gap these trends are creating, their repercussion on salaries and where the require for expertise is headed.

  • By David Foote
  • 12/05/2016
  • It's difficult to find an employer not struggling to attain up with a unique tech staffing model that balances three things: the urgencies of original 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 exist 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, commodious Data advanced analytics, cybersecurity, and original mobile and cloud computing capabilities. Consequently, tech professionals and developers must align their skills and interests accordingly to attend 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 any 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 occupy many IT managers aphorism they can't find adequate labor to attend them protect their existing networks and endpoints. The latest reminder was in the spotlight following the most powerful denial of service (DoS) assail to date in late October resulting from unprotected endpoints on surveillance cameras. IoT, machine-to-machine communications and telematics occupy introduced original complexities ranging from the necessity to better secure the devices and the delivery points to which they connect. Meanwhile, the growing IoT landscape is unleashing an exponential flood of original data from hundreds of millions of devices, and organizations necessity to blend their IT and operational systems and find people with commodious Data analytics skills to handle the cloud-based machine learning infrastructure that's now emerging. This generational shift in IT will achieve a premium on, or create a baseline requirement for, IT professionals willing to supervene the money and espy where their skills will exist 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 significant to understand that the supply-and-demand aspect that drives compensation is moreover a stirring target. IT pay has a long history of volatility and in 2016 they occupy seen even sharper swings in those premiums. Based on hiring patterns, the following overriding trends will drive market require for IT professionals who occupy the experience, drive and skills to deliver solutions:

  • Cybersecurity: The necessity 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 exist sturdy for the coming years as the threat landscape continues to become more intricate and confounding. The elimination of traditional boundaries brought about by cloud computing and mobility and a massive original 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 coalesce of the two. The scamper to these elastic infrastructures and op-ex approach to IT is moreover enabling high-performance computing and storage capacity that's ushering in the talent to perform workloads and software-defined automation not feasible with traditional client server or Web application tier infra­structures. Likewise, the scamper to cloud service-based apps such as Salesforce, Office 365 and Workday, to name just a few, is shifting the necessity for those with skills in edifice and managing traditional packaged software to those skillful in these original 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 scamper toward digital transformation is any about empowering users to create quick decisions based on an overwhelmingly massive groundswell of data to exist curated from original 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 scamper to digital transformation, or at least the method to execute so, means organizations must exist more agile. A more rapid release cadence in software delivery -- from Windows and Office to open source environments and perpendicular applications -- requires that IT shops can build, deliver and manage systems with these dynamics. Likewise, original programming environments and frameworks such as containers and micro-services are enabling original classes of cloud-native applications designed for original classes of devices and bright and modern infrastructure.
  • Digital industry Transformation: This is the cessation 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 renowned but moreover includes the talent to leverage advances in UX and UI design and the talent to lever­age IT to attend companies build original products, services and champion 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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    Operations & Process Management: Principles & Practice for Strategic ImpactOperations & Process Management: Principles & Practice for Strategic Impact
    By Nigel Slack, Alistair Jones
    Publisher : Pearson (Feb 2018)
    ISBN10 : 129217613X
    ISBN13 : 9781292176130
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    Subject : Business & Economics
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    Computer Security: Principles and PracticeComputer Security: Principles and Practice
    By William Stallings, Lawrie Brown
    Publisher : Pearson (Aug 2017)
    ISBN10 : 0134794109
    ISBN13 : 9780134794105
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    Subject : Computer Science & Technology
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    Urban EconomicsUrban Economics
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    Publisher : McGraw-Hill (Jan 2018)
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    Urban EconomicsUrban Economics
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    Understanding BusinessUnderstanding Business
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    Publisher : McGraw-Hill (Feb 2018)
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    Publisher : McGraw-Hill (Jan 2018)
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