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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 Name : DB2 10.1 DBA for Linux UNIX and Windows
Vendor Name : IBM
Q&A : 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 new 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 decide upon most fulfilling patterns and passes this advice to the Db2 query optimizer for use by means of subsequent statements.

laptop getting to know on the IBM z Platform

In may also of 2018, IBM announced version 1.2 of its machine gaining knowledge 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 make use 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. equipment management Facility (SMF) data that are instantly generated by the working equipment supply the raw statistics for equipment aid consumption comparable to critical 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, increase key efficiency warning signs (KPIs) and then feed the mannequin outcomes returned into the device to have an effect on system configuration changes that can enrich performance.

    The next step was to implement this suite to analyze Db2 efficiency statistics. One solution, called the IBM Db2 IT Operational Analytics (Db2 ITOA) answer 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 normal utility health and performance, IBM estimates that the DBA aid body of workers spends 25% or greater of its time, " ... fighting access route issues which cause efficiency degradation and service have 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 have to assist one or extra big 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 be accessed and develops an inventory of candidate information entry paths. These entry paths can include indexes, table scans, numerous table be part 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 include pre-summarized or aggregated information, for that reason enabling Db2 to keep away from re-aggregation processing. a different option is the starjoin entry path, normal 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 charge 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 business analyst to use 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 do 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 mature body of workers nearing retirement?

    be mindful additionally that a large part of reducing the full can charge of ownership of those methods is to get Db2 purposes to run 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 place computer discovering and synthetic intelligence will also be used to terrific impact.

    Db2 12 for z/OS and synthetic Intelligence

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

    The effect should be a reduction in CPU consumption because the Optimizer makes use of mannequin scoring input to choose improved entry paths. This then lowers CPU prices and speeds application response instances. a significant competencies is that the use of AI utility does not require the DBA to have statistics science knowledge 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 also be specifically important if you keep information in assorted locations. as an example, many analytical queries in opposition t big statistics require concurrent access to definite statistics warehouse tables. These tables are often referred to as dimension tables, and they contain the facts features usually used to handle subsetting and aggregation. for instance, in a retail environment accept as true with a table known as StoreLocation that enumerates each save and its location code. Queries towards keep sales records might also want to aggregate or summarize income by using location; hence, the StoreLocation desk might be used by way of some large data queries. during this atmosphere it's normal to take the dimension tables and copy them always to the big statistics application. in the IBM world this region is the IBM Db2 Analytics Accelerator (IDAA).

    Now consider about SQL queries from each operational purposes, data warehouse clients and large statistics business analysts. From Db2's standpoint, all these queries are equal, and are forwarded to the Optimizer. youngsters, within the case of operational queries and warehouse queries they should still certainly be 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 knowledge entry paths, and more work for the Optimizer. fortuitously, Db2 AI for z/OS can give the Optimizer the assistance it must make smart access direction choices.

    the way it Works

    The sequence of hobbies in Db2 AI for z/OS (See Reference 2) is often right 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 knowledge of assignment, which may also be 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 also can be 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 also 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 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 help group of workers need to be 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 do you know your facts, its distribution, its integrity and your latest and proposed entry paths? this will determine the place the DBAs spend 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 use IBM records Studio. Toad DBA Suite for IBM DB2 LUW complements facts Studio with advanced features that make DBAs and developers a lot more productive. How can Toad DBA Suite for IBM DB2 LUW advantage 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 whole checklist of computing device discovering options

    final analysis

    RapidMiner may also now not have 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 also 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 knowledge of. The solution also 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 knowledge of from a holistic viewpoint and presents a large number of equipment to handle myriad projects. The platform helps all important 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 way of URL. It helps NoSQL, MongoDB and Casandra, and its Radoop product extends information environments into the open supply Hadoop space.

    This makes it possible to generate and re-use current R and Python code, and mix and recombine current modules with new extensions and modules. The platform also 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, business 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 Excel and access, CSV, and database connections. presents access to NoSQL databases MongoDB and Cassandra.

    Integration

    guide for all 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 small 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 ideal for businesses aiming to use 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 describe it as effective 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 Use 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 face it: it’s IBM software. It has a pretty long history. You would probably not expect that it is easy 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 be another surprise: there is a free community edition. It’s not open source, but it’s free as in free beer.

    No Easy Explain

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

  • Explain a statement by prefixing it with explain plan for

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

  • Display a stored explain plan using db2exfmt

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

  • There is another command line tool (db2expln) that combines the two steps from above. Apart from the fact that this procedure is not exactly convenient, the output you get 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 full output of db2exfmt has 400 lines. Quite a lot information that you’ll hardly ever need. Even the information that you need all the time (the operations) is presented in a pretty unreadable way (IMHO). I’m particularly thankful that all the numbers you see 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 way to display an execution plan: “Write your own queries against the explain 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 plan of the last statement that was explained (in a non-useless formatting):

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

    I’m pretty sure many DB2 users will say that this presentation of the execution plan is confusing. And that’s OK. If you are used to the way IBM presents execution plans, just stick to what you are used to. However, I’m working with all kinds of databases and they all have a way to display the execution plan 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 count estimates and the predicate information.

    You can get the source of the last_explained view from here or from GitHub (direct download). I’m serious about the no warranty part. Yet I’d like to know about problems you have with the view.

    Emulating Partial Indexes is Possible

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

  • To preserve space when the index is only useful for a very small 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 like the following can be 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 support a where clause for indexes like 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 all parts of the index key contain 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 all parts of the key (all indexed columns) to NULL for rows that should not end 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 function 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 RETURN receiver; ELSE RETURN NULL; END IF; END; /

    It’s a deterministic function and can thus be used in an Oracle function-based index. This won’t work 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 function returns NULL which is not put in the index (there is no other column that could be non-NULL). Voilà: a partial index in the Oracle database.

    To use this index, just use the pi_processed function 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 make this approach work in DB2 we need two components: (1) the EXCLUDE NULL KEYS clause (no-brainer); (2) a way to map processed rows to NULL without using a user-defined function so it can be used in a DB2 index.

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

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

    This implements the very same mapping as the pi_processed function above. Remember that CASE expressions are first class citizens in SQL—they can be 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 be indexed rows to NULL and the EXCLUDE NULL KEYS feature to prevent those row from being stored in the index. Voilà: a partial index in DB2 LUW 10.5.

    To use the index, just use 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 | RETURN | | 49686 2 | TBSCAN MESSAGES | 900 of 999999 ( .09%) | 49686 Predicate Information 2 - SARG (Q1.PROCESSED = 'N') SARG (Q1.RECEIVER = ?)

    Oh, that’s a big disappointment: the optimizer didn’t take the index. It does a full table scan instead. What’s wrong?

    If you have a very close look at the execution plan above, which I created with my last_explained view, you might see something suspicious.

    Look at the predicate information. What happened to the CASE expression that we 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 use 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 good understanding what they do and can transform them.

    We need a way to apply our magic NULL-mapping but we can’t use functions (can’t be indexed) nor can we use CASE expressions, because they are optimized away. Dead-end? Au contraire: it’s pretty easy to confuse an optimizer. All you need to do 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 use this expression in the index and the query, I get this execution plan:

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

    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 like in more recent Oracle versions).

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

    INCLUDE Clause Only for Unique Indexes

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

  • In SQL Server INCLUDE 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 also allows to bypass some limitations (number of columns, total index row length, allowed data types). That doesn’t seem to be the case in DB2.

  • In DB2 the INCLUDE clause is only valid for unique indexes. It allows you to enforce the uniqueness of the key columns only—the INCLUDE columns are just not considered when checking for uniqueness. This is the same in SQL Server except that SQL Server supports INCLUDE 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 standard doesn’t specify a default. As you can see 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 also see 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 true for ORDER BY col DESC NULLS LAST—accepted, but doesn’t change anything. The other two combinations are not valid at all and yield 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 look like an arbitrary omission, it is in fact a very wise move that I deeply respect. offset is the root of so much evil. In the next section, I’ll explain how to live without offset.

    Side node: If you have code using offset that you cannot change, you can still activate the MySQL compatibility vector that makes limit and offset available in DB2. Funny enough, combining fetch first with offset is then still not possible (that would be standard compliant).

    Decent Row-Value Predicates Support

    SQL row-values are multiple scalar values grouped together by braces to form a single 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 poor 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 like 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 get the next few ones. For that you’d use the time_stamp value of the last entry you’ve got for the bind value (?). The query then just return 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 place till where you have the result. This is where row-value predicates come 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 make sure 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 be 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 standard since 1992! However, it is possible to apply the same logic without row-value predicates—but that’s rather inconvenient and easy to get wrong.

    Even if a database understands the row-value predicate, it’s not necessarily understanding these predicates good enough to make proper use of indexes that support the order by clause. This is where MySQL fails—although it applies the logic correctly and delivers the right result, it does not use 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 way it should be.

    The fact that DB2 LUW has everything you need for convenient keyset pagination is also the reason why there is absolutely no reason to complain about the missing offset functionality. In fact I think that offset should not have been added to the SQL standard and I’m happy to see a vendor that resisted the urge to add it because its became part of the standard. Sometimes the standard is wrong—just sometimes, not very often ;) I can’t change the standard—all I can do is teaching how to do it right and start campaigns like #NoOffset.

    Figure A.2. Database/Feature Matrix

    If you like my way of explaining things, you’ll love my book “SQL Performance Explained”.


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

    Chances are, you have never heard of Amanda… in the sense of open source that is. And if you have not heard of Amanda, then chances are you have not heard of Zmanda either. I will explain both, and I will give you my view of why it is important for you to at least be aware of these products and their relation to data protection. Whether you should invest in either depends on many factors that will become clear 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. Like most free downloads, these usually come from universities -- both students and IT folks -- and scientific labs. But, they also include 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 run 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 have contributed to its development, bug fixes and its general care and feeding. As a result, the usage of the product has continued to climb dramatically over the past few years.

    You can use Amanda for free. You can modify it and put it back in the ether for free. But, like all open source software, if the software just stopped running in the middle of the night because your client application server was not yet supported, good luck trying to get support. Or anything else. Your best bet would be to place your request on one of many Web sites where users and developers help each other out.

    But, unlike Linux operating systems (where there are companies like RedHat and SUSE, which is now Novell) or Linux-based databases (where there are companies like mySQL), Amanda did not have a "for profit" sponsor until recently. In late 2005, a newly-formed company was charged with working to make Amanda a more usable product that would be able to support enterprises of all 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 last six months, Amanda has come a long way. But, it also has a long way to go before I would consider it a full member of this class. Should you therefore ignore it? No. However, the reason I am writing this column is to make you aware that, under the right 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 like any other open source product. Of course, the whole idea is to price 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, ask yourself the following questions:

  • Does the current product have support for my systems?
  • Does it have the features I need?
  • Does the product have support for my applications (e.g., Oracle, SQLserver, and DB2?)
  • Does it have adequate disk support?
  • What about archiving?
  • I am sure that as you look into these options you will have other questions that are specific to your organization's needs. Version 2.50 of Zmanda does have support for Windows and Linux, but not for all popular flavors of Unix. It should support databases and other applications in the future but does not right now. It also lacks a GUI and does not yet support all the new innovations that we have seen in the world of disk support (like VTL and CDP). But, it does have disk support. It also has some features that I wish we had in the other commercial offerings, like a non-proprietary data format and like having the ability to do a recovery without requiring the vendor's software. Of course, its Linux support 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 we have 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 make a pretty reasonable argument that data protection software from all the major vendors had become pretty bloated, and the rate of innovation was very slow. Adding support for a new tape library does not count as innovation in my book. It is precisely at such times, when differentiation between vendors' products is low, that open source starts to make 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 like 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 be to not only create the old tape-based functionality but also to add all the new juicy disk-based functionality that is coming in waves currently. I suspect it is up for the challenge but at least be aware that there could be a lag before you see all 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 have simpler needs, cost is a major issue and you crave that freedom from the big vendor -- for whatever reason -- then you should check out this new space. But my advice: Do not run a production environment without the support that comes with Zmanda. Amanda may be free, but she can be trouble 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, Big 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 impact on salaries and where the demand for expertise is headed.

  • By David Foote
  • 12/05/2016
  • It's difficult to find an employer not struggling to come up with a unique tech staffing model that balances three things: the urgencies of new 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 choose 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 be 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, Big Data advanced analytics, cybersecurity, and new mobile and cloud computing capabilities. Consequently, tech professionals and developers must align their skills and interests accordingly to help 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 all 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 have many IT managers saying they can't find adequate labor to help them protect their existing networks and endpoints. The latest reminder was in the spotlight following the most powerful denial of service (DoS) attack to date in late October resulting from unprotected endpoints on surveillance cameras. IoT, machine-to-machine communications and telematics have introduced new 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 new data from hundreds of millions of devices, and organizations need to blend their IT and operational systems and find people with Big Data analytics skills to handle the cloud-based machine learning infrastructure that's now emerging. This generational shift in IT will put a premium on, or create a baseline requirement for, IT professionals willing to follow the money and see where their skills will be 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 important to understand that the supply-and-demand aspect that drives compensation is also a moving target. IT pay has a long history of volatility and in 2016 we have seen even sharper swings in those premiums. Based on hiring patterns, the following overriding trends will drive market demand for IT professionals who have 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 be strong for the coming years as the threat landscape continues to become more complex and confounding. The elimination of traditional boundaries brought about by cloud computing and mobility and a massive new 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 mix of the two. The move to these elastic infrastructures and op-ex approach to IT is also enabling high-performance computing and storage capacity that's ushering in the ability to perform workloads and software-defined automation not possible with traditional client server or Web application tier infra­structures. Likewise, the move to cloud service-based apps such as Salesforce, Office 365 and Workday, to name just a few, is shifting the need for those with skills in building and managing traditional packaged software to those proficient in these new 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 move toward digital transformation is all about empowering users to make quick decisions based on an overwhelmingly massive groundswell of data to be curated from new 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 development is taking hold as the move to digital transformation, or at least the plan to do so, means organizations must be 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, new programming environments and frameworks such as containers and micro-services are enabling new classes of cloud-native applications designed for new classes of devices and intelligent and modern infrastructure.
  • Digital Business Transformation: This is the end goal of many organizations that fear, rightfully so, their business models are at risk unless they can become digital businesses. This is the culmination of the four areas just noted but also includes the ability to leverage advances in UX and UI design and the ability to lever­age IT to help companies build new 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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