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C2090-612 - DB2 10 DBA for z/OS - BrainDump Information

Vendor Name : IBM
Exam Code : C2090-612
Exam Name : DB2 10 DBA for z/OS
Questions and Answers : 134 Q & A
Updated On : January 17, 2019
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C2090-612 exam Dumps Source : DB2 10 DBA for z/OS

Test Code : C2090-612
Test Name : DB2 10 DBA for z/OS
Vendor Name : IBM
Q&A : 134 Real Questions

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IBM IBM DB2 10 DBA

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IBM Db2 on Cloud (which begins at $189 per 30 days) is a smartly-designed, wholly managed SQL Database-as-a-carrier (DBaaS) solution with Db2 and Oracle PL/SQL compatibility. records migration approaches and the user interface (UI) are clear, intuitive, and easy to function for clients of numerous skill levels. The product is best for developers who want to create a database devoid of the guidance of a database administrator (DBA). or not it's also exquisite for company analysts who wish to custom construct a database very quickly flat.

IBM Db2 on Cloud is a great offering that receives a 4.0 ranking in this evaluate for its sheer ease of use. youngsters, some developers chafe at the barriers in design control, notably when compared with the severe flexibility of Editor's alternative MongoDB Atlas in offering tons of controls for developers. IBM Db2 on Cloud additionally falls in need of Editors' choice Microsoft Azure SQL Database, which seriously outpaces IBM Db2 on Cloud in the number of areas—a big deal in some situations when it comes to software performance and compliance with the european Union (eu)'s established records coverage regulation (GDPR). despite the fact, IBM Db2 on Cloud presents greater regions than either Amazon Relational Database service or Google BigQuery.

Pricing model

clients are funneled into the free Lite tier as a place to begin. The database then recommends both IBM Db2 on Cloud (SQL) or Cloudant (NoSQL) in accordance with the statistics. or not it's obvious that the IBM Db2 on Cloud designers discovered lots from the Bluemix team because IBM Db2 on Cloud outpaces Rackspace's ObjectRocket (NoSQL) and Amazon Relational Database carrier (Amazon RDS) in ease of use, principally in records migration. each ObjectRocket and AWS RDS are most efficient used with the aid of a DBA, at the least all through setup. against this, most users could be able to spin up a database in IBM Db2 on Cloud with little fuss, except, of route, the fuss comes from a DBA. Let's face it. DBaaS frequently quantities to legitimized shadow IT and not everybody in it's a fan. or not it's premier to assess your company's policy on using a DBaaS and follow the prescribed protocols.

The respectable news is that there is a free Lite plan limited to a hundred megabytes (MB), five connections, and one schema. that you could create diverse Lite plans if you need. No bank card is required whether you employ one or varied Lite plans. The Lite plan is a groovy approach to check out the service, study greater about working with databases, or do smaller jobs for gratis. there may be also a free developer community edition with enterprise points. Db2 specific-C is free for business use however is hobbled a bit of by way of the shortcoming of some advanced commercial enterprise facets.

The paid Flex plan for IBM Db2 on Cloud starts at $189 monthly for 1 core, four gigabytes (GB) of random access reminiscence (RAM) and a couple of GB of disk storage. additional cores are $52 per core per 30 days. Or $13 per GB of RAM, in view that each and every core has 4 GB of RAM. extra disk storage is $1 per GB per month. for prime availability, you should double the base plan, cores, and storage can charge. And the last line item on the bill is a can charge of $0.20 per 1 million enter/output (I/O) operations performed.

you probably have IBM Db2 on-premises, then you definitely get a huge discount using IBM's "bring Your own License" application. Contact your IBM rep for details. you can additionally get a reduction on an IBM Cloud subscription.

step by step

After establishing an account on IBM Cloud, go to the Menu icon at the higher left-hand side of the monitor to stream to the dashboard and click on on "Create aid." From there, you're employed through a sequence of alternate options for setup. My setup changed into US South vicinity, Db2 on Cloud, after which Flex Plan. It takes 30 seconds to a minute to create a brand new illustration.

IBM Db2 on Cloud has one of the most least difficult information-loading approaches in our DBaaS solutions assessment roundup. I loaded the data with one click on on the console web page, followed with the aid of a drag and drop of my CSV verify records. one more click is required in case you choose to make use of Aspera for a high-speed load. next is a call of two schemas or the alternative to create your personal. A schema is a set of tables to arrange the statistics. IBM Db2 enables assorted schemas for each and every database. For this test, I chose the IBMADT schema alternative. The equipment then presents the alternative to select or create a desk. next is the outline table stage. word in the screenshot under that formats have pull-down menus and effortless counsel and suggestions below the "?" icon by each and every layout category. When those tasks are accomplished, the facts starts uploading.

once the information is uploaded, click on the Run SQL tab, and you're off and working. which you can either enter SQL statements in the SQL editor or load a SQL script from the toolbar. I had no issues with the setup and changed into up and operating with minimal effort. To scale up, I necessary most effective to return to the console and click on the scale instance button. There i will be able to use a slidebar to scale up or down. The console immediately shows compute and storage scaling particulars in addition to an estimated new cost.

The Toolbox

In IBM Db2 on Cloud, you may not discover computer tools to install or complicated cloud configurations to be troubled your means through. Make one click on on alternatives like "high availability" or "Oracle compatibility mode" and also you're first rate to move. Use the weight wizard within the internet console to import a spreadsheet, and IBM Db2 on Cloud will make counsel for each column that you could spark off or regulate. bear in mind this is a relational database so that you can only use structured data like you'll discover in a spreadsheet. however that doesn't mean the facts dimension must be small. in fact, it will also be fairly massive. you probably have a lot of records emigrate, then you definately have alternate options to speed the switch. IBM Aspera each compresses your statistics and uses the person datagram protocol (UDP) to optimize your information superhighway line. UDP makes low-latency, loss-tolerating connections and consequently is an awful lot quicker than the option transmission manage protocol (TCP). you will locate it as a browser plug-in on the net console. this can render two to 5 instances the general speed of your web connection. For significant, complex databases, use the free IBM carry tool.

in the event you have been questioning, IBM joins IBM Db2 on Cloud records with that of IBM Watson Analytics within the equal approach as another records supply. IBM has a separate NoSQL cloud-based mostly database referred to as Cloudant (which I in short outlined previous). if you are using IBM Cloud, then you definately also have the choice of the use of IBM Compose, the place that you can choose among 10 open-source databases: Elasticsearch, JanusGraph, MongoDB, MySQL, PostgreSQL (aka Postgres), RabbitMQ, Redis, ScyllaDB (Apache Cassandra), etcd, and RethinkDB.

keep in mind that you simply use IBM Db2 on Cloud by way of importing spreadsheets via a web console and then run SQL from there. it truly is the point of DBaaS: no configurations vital. but, really, any third-birthday celebration equipment you could be the use of now with IBM Db2 on Cloud on-premises (akin to FalconSQL, SQuirreLSQL, or Toad for IBM Db2) work with IBM Db2 on Cloud. vigour users have two added options, IBM statistics Server supervisor and IBM information Studio. IBM facts Server manager displays and analyzes distinctive IBM Db2 on Cloud cases, on the floor or within the cloud. It additionally helps open-supply databases. IBM data Studio is DBA computer application for superior clients, that means generally DBAs.

Being able to select the regional location in your database is critical for two motives. First, because of rules such because the GDPR, you must make certain of where your information resides (even within the cloud), the place it strikes to, and the way it's used. Being in a position to select the appropriate location for your database is necessary to preserving compliant. Secondly, the closer your data and app are to one a different, the stronger the performance (the shorter the lag and different considerations). you're going to are looking to seek alternatives to install your app in the identical facts center as your database, or colocate your database subsequent to your app.

IBM Db2 gave me 22 vicinity alternatives, including Amsterdam, Chennai, Dallas, Frankfurt, Hong Kong, London, Melbourne, Milan, Montreal, Norway, Paris, Querétaro (Mexico), San Jose, Sao Paulo, Seoul, Singapore, Sydney, Tokyo, Toronto, and Washington, D.C.

although, the free Lite edition runs only from IBM's Dallas records core, but the seven-day free trial version works in any of these 22 locations. excessive availability plans come with a a 99.99 p.c uptime provider-stage agreement (SLA) whereas single-server plans offer a smaller 99.95-% uptime SLA. IBM Db2 provides 14 days of daily backups.

whereas no system is ultimate or ideal for every goal, IBM Db2 on Cloud is usually strongly liked by using people that need greater convenience and ease of use than is commonly found in database items or features. although some developers may additionally locate IBM Db2 on Cloud design controls limiting, they're going to enchantment to admins for the steadiness and consistency they deliver to the database usual.

IBM Db2 on Cloud

spectacular

base line: IBM Db2 on Cloud is a dream Database-as-a-carrier (DBaaS) solution for developers and company analysts as a result of they can use it with out the assistance of a database administrator, even with minimal potential.


the way to Migrate On-Premise Databases to IBM DB2 On Cloud | killexams.com Real Questions and Pass4sure dumps

MariaDB TX, proven in construction and pushed via the group, is a complete database solution for any and every enterprise — a latest database for up to date applications.

Introduction

Database migration can appear elementary from backyard, particularly, get the supply records and import/load to the target database, but the satan is at all times in the particulars, and the route isn't that elementary. A database carries more than just the information. A database can consist of a variety of — however often related — objects. With DB2, two types of objects can exist: equipment objects and statistics objects. let's see what they are, and in a while within the article, one of the crucial principal objects are mentioned from caution views during planning and migrating.

many of the primary database engines offer the identical set of fundamental database object types: (please examine moreover on these object varieties from respective providers. The definition and function could be extra or less equivalent. An analogy is that you just power vehicles, and for those who stream from one vehicle to a further, the fundamentals of vehicles stay the same, however differences include ignition buttons, home windows, structure as a whole, etc., however the useful use and base of the car continues to be the same, like 4 wheels, engines, chassis, etc.)

  • Tables
  • Indexes
  • Sequences
  • Views
  • Synonyms
  • Indexes
  • Alias
  • Triggers
  • consumer-described records types (UDTs),
  • consumer-described capabilities (UDFs)
  • kept strategies
  • programs
  • gadget Objects include:

  • Storage organizations
  • Tablespaces
  • Buffer swimming pools
  • system Catalog tables and views
  • Transaction log info
  • These objects at on-premise databases should take delivery of correct care whereas planning migrations. It is awfully essential to take into account what can also be migrated and what can't due to the fact that there should be would becould very well be a necessity for skilled features from a third birthday party or from a cloud seller in doing so.

    What Can and might't Be Migrated?

    everyday SQL consumer-defined services (UDFs) can be migrated however external UDFs could have some issue being migrated. external UDFs may be written in C, C++, or Java and then compiled in some situations to kind a library and sit down at a exact vicinity and would should be registered with DB2. So, exterior UDFs deserve to be rebuilt on cloud servers as a result of OS versions can be diverse on the goal. Migrating such UDFs may want database migration functions from cloud companies or they can not be migrated to cloud. in a similar way, SQL kept techniques may also be migrated to the target Database, but exterior keep techniques will elevate the identical constraints than that of UDF and will no longer be supported. Materialized query desk(MQTs) will also be migrated, but they should still be created after the statistics is moved to the goal database. similarly, the triggers can also be migrated when information is moved to goal database. The hyperlink between system-duration temporal tables and their associated historical past tables ought to be broken before the table's facts can also be moved (this holds proper for bitemporal tables). A gadget-length temporal desk is a table that keeps historical models of its rows. Bitemporal Modeling is an information modeling approach designed to deal with old data along two different timelines. A bitemporal desk is a desk that mixes the historical tracking of a device-length temporal desk with the time-particular records storage capabilities of an application-period temporal table. Bitemporal tables are generally used to maintain user-based duration assistance in addition to system-based ancient counsel.

    Now we've some thought on what emigrate and what now not to. Database directors should are seeking for some downtime while performing this. relevant planning and cautions may still be taken while performing each and every of the mentioned actions, and correct time should be dispensed to have in mind the nature of migration. Let me additionally element out a big constraint with migration to DBaaS or DB on circumstances on cloud (from equipment Object PoV): just one buffer pool can be supported and the user areas should be merged with main person house with one buffer pool emigrate to the goal state. dissimilar user spaces with distinct DB swimming pools and buffer pools should not supported for DBaaS or DB on instance (VM) on cloud. So, bear in mind that!

    Now we would delivery the migration. There are definite tools developed from IBM to perform migration projects, and the vital ones are db2look utility and IBM Optim high efficiency sell off. Db2look utility is used for generating new information Definition Language (DDL) statements for goal DB2. IBM Optim excessive performance unload can function copying the existing Database to a brief folder/bucket, which can also be AWS S3 or Softlayer Swift. The identical device will also be leveraged to paste through import/load utility to the target.

    The quite a few ways to stream records to DB2 on cloud — DB2 hosted, DB2 on cloud and DB2 warehouse on cloud are given below:

  • Load records from a native file kept on the computing device (using #Bluemix interface)
  • Load records from a Softlayer swift object keep (the usage of #Bluemix interface)
  • Load records from Amazon S3 (the usage of #Bluemix interface)
  • Use the DB2 records stream utilities, remotely
  • Use the IBM records transfer carrier (25 to 100TB)
  • Use the IBM Mass statistics migration provider (100 TB or more)
  • Now comes the security aspect whereas migrating, encryption the use of AES or 3DES is advised. SSL and TLS are the favored how to cozy information in transit.

    Let’s additionally shed some light on DB2’s native encryption and how it really works.

  • customer requests an SSL connection and lists its supported cipher suites (AES, 3DES)
  • Then, the server responds with a particular cipher suite and a copy of its digital certificates, which contains a public key.
  • client tests the validity of certificates — if it is legitimate, a session key and a message authentication code (MAC) is encrypted with a public key and sent again to the server.
  • Server decrypts the session key and MAC (message authentication code), then send an acknowledgment to start an encrypted session with the customer
  • Server and client securely change data the usage of the session key and MAC chosen.
  • These are probably the most essential facets to be regarded while migrating on-premise databases to IBM DB2 on Cloud.

    suppose free to share your views within the feedback. 

    MariaDB AX is an open supply database for contemporary analytics: disbursed, columnar and straightforward to make use of.

    issues:

    ibm db2 ,database migration ,database ,ibm ,ibm cloud


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    DB2 10 DBA for z/OS

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    Big Data: Health Checking Your System | killexams.com real questions and Pass4sure dumps

    As big data solutions grow in size and complexity, concerns can rise about future performance. Will the current application scale up and out? Are there potential issues with data consistency? Can your big data application co-exist on the same hardware with regular production processing, or is it destined to be implemented in either a stand-alone configuration or in the cloud? One way to assess the potential effects of these issues is to measure your big data application’s health.

    In the Beginning

    Early big data solutions were presented as stand-alone, turnkey systems that required no performance tuning and promised “crazy fast” query execution times. Very little support from database administrators (DBAs) or systems programmers was required.

    For a few years and for most IT shops, this held true. However, the number of analyzable data types grew (think XML, video, click-streams) and the time range of business queries expanded from current month to recent months to year-over-year. Total data volumes in some businesses grew beyond the 100 terabyte range, while at the same time queries that originally were executed only once morphed into regular reports.  Performance began to degrade. Tuning became a necessity.

    Big Data on Db2

    IBM’s flagship entry into the big data arena is the IBM Db2 Analytics Accelerator (IDAA). This was originally presented as a hybrid hardware/software solution with a proprietary data store and highly parallelized I/O processing. The Db2 Optimizer was enhanced to consider tables stored in the IDAA as alternatives for query data access paths. For example, the DBA may choose to store a Customer table in both native Db2 and the IDAA. Any query that accesses the Customer table is analyzed by the Db2 Optimizer, which then decides which of the table occurrences will provide the best query performance. Thus, real-time queries that require a single row from the Customer table will get their data from the table in Db2, while analytic queries may be directed to the table in IDAA.

    Later versions of IDAA allowed the DBA several possible ways to affect query execution, including data clustering and data partitioning options. The DBA became more and more involved in configuring the IDAA, and consequently needed to understand current and potentially future data access options by user queries. Consequently, the DBA was now in a position to resolve performance and health issues.

    The latest upgrade to IDAA allows it to run natively on z14 hardware using a logical partition (LPAR) called the z Secure Service Container. Embedding such specialized storage and processing directly into the mainframe configuration means that the hardware and accompanying operating systems software can process both on-line transactions and business analytics queries at the same time, sometimes called hybrid transactional and analytic processing (HTAP).

    The Health of Your Big Data System

    Today, the DBA is intimately involved with configuration and tuning of the big data application, partly because vendors responded to their concerns by upgrading solutions to include options such as data clustering and data partitioning. Still, performance tuning is only one aspect of the health of a system.

    Application or system health is a combination of the user experience and resource utilization. While there are other items that are relevant to application health in general (such as data availability and consistency and various integrity rules), these are rarely an issue in a big data environment as the data loaded there originates from operational systems.

    We concentrate on these two points because they may be affected the most as big data configuration options expand, data volumes increase and the needs of the business analysts change over time.

    User Experience

    Generally speaking, the big data user differs from users of other systems (including the data warehouse) in several ways. Business analysts typically use a specialized software interface that displays big data entities and relationships in one or more visual formats, allowing the user to point-and-click or drag-and-drop choices of data items, selection options, aggregation criteria, analysis time periods and the like. The software then constructs the appropriate query or queries, accesses the data and returns the results, usually in tabular or pictorial form.

    The user’s experience is tied directly to their software package, and not to the SQL query generated. This makes query performance tuning somewhat difficult, as users are not usually aware of the underlying query syntax. Further, their software may hide from them any available performance options such as keys, clustering, indexes or other features. What the user notices the most is query response time.

    To address the user experience, the DBA can use several methods to monitor the health of their big data application.

    Query Tuning: While it may be difficult (or impossible) to predict what queries may be generated by business analytics software tools, the DBA can still make use of historical access patterns. What tables are accessed, and how frequently? What tables are commonly joined? Which tables are dimension tables (used for aggregations, subsetting and sorting) and which are fact tables (used for calculations)? What access paths are typical? Is the starjoin access path (typical in data warehouse applications) used at all?

    Typically, the DBA will use a tool to capture historical SQL statements and their access paths. This can be done in Db2 via the dynamic statement cache and the Explain tool. Then, store the results in a set of performance history tables. Repeat on a regular basis. You can then query the results to answer the above questions. Commonly accessed tables might be stored both in native Db2 and IDAA. Commonly joined tables should be clustered and partitioned in a similar manner to take advantage of parallelism. Common data item aggregations can be pre-computed and stored in tables themselves (sometimes called summary tables or materialized query tables), providing for faster queries that aggregate these items.

    Query the performance history tables to determine if the same access path(s) are used to access the same tables. If not, are any of the access paths faster, and can objects or queries be tweaked to take advantage of them?

    Data Archival: Another method of addressing perceived slowness of queries is to remove stale or old data or place it in a secondary set of tables. For example, consider a table of customer transactions over time. Keep the most current data in a Current Customer Transactions table, move the prior three months of data to a Recent Customer Transactions table, and place the oldest in a Historical Customer Transactions table. By splitting the data this way, queries acting upon current or mostly current data will access fewer tables, and thus save data processing time.

    Another method of archival is a form of what is called vertical partitioning. Review the columns in a commonly accessed table and split them into two categories based upon how often they are referenced in queries. Place frequently accessed columns in one version of the table, infrequently accessed columns in another. As with archival, queries that select only frequently accessed columns will reduce the number of I/Os necessary to retrieve what is needed.

    Customized Environments: Users across an enterprise can use big data for completely different purposes. Ad hoc users create new queries, or slightly modified versions of current ones. Reporting users run and re-run current queries on a regular basis to provide reports to management. Data mart users take regular extracts of big data and load them into their own local databases for intensive analysis. Each category of user accesses big data in a different way, so each has a different experience.

    The ad hoc user requires the most intensive support from the DBA. Here, it is important to gather and maintain historical table usage and access path data. Single query execution speed is the most important factor, and the DBA will most likely be tuning objects (through archival, clustering, partitioning, etc.) rather than tuning SQL. On some occasions, there will be SQL issues. This is because the business analytics software may not be generating the highest quality query syntax. Some software vendors have features that allow your support staff to make minor changes to certain categories of SQL statements, or to certain clauses. Clauses such as OPTIMIZE FOR n ROWS or FETCH FIRST n ROWS can be appended to some queries, while the software can be configured to recognize things such as summary tables.

    The reporting user exists in a much more static environment. Here, the reporting queries executed are typically stored in a format that allows for editing. Thus, if the DBA is aware of a better way of coding the query, they can make the appropriate changes.

    Data mart users typically extract from the big data application because the data there has already been extracted, cleaned, transformed and loaded from operational systems. While this is a convenience for the data mart user, it may be a faster option to have them extract data directly from operational systems. The processes already exist for big data, and probably also for your data warehouse, and they can be modified appropriately to send data to the data marts as well.

    Resource Utilization

    Resource utilization drives costs in several ways. Applications’ needs for CPU, memory, disk space and network bandwidth drive the direct costs of purchasing, installing and maintaining these resources. Implementing IDAA as a stand-alone hybrid has the effect of offloading CPU cycles from the mainframe. Extracting data to a remote data mart for processing can have a similar effect.

    One common issue regarding disk space is the enormous amount of space provided in big data solutions. Space in the hundreds of terabytes are common. When your big data application receives its first load of data much of that space remains unused. It is therefore a great temptation to use it as storage for other things. Some examples include archive tables, database backups, and space for multiple environments such as development, test and production.

    If you allow things other than big data to be stored in the IDAA you must take into account the future usage of the device and the environment. One such consideration is disaster recovery. Most mature big data applications can be accessed directly from production systems for things such as credit analysis, product buy recommendations or fraud detection. As such, your big data environment may need to be replicated in some manner at your disaster recovery site, perhaps thereby doubling the amount of resources you need to acquire. Implementation of your big data in a robust disaster recovery environment is critical for the health of your overall system.

    Another issue is software costs. Some software is priced based upon CPU usage. Typical examples in the IBM world are the z/OS operating system, Db2, and Cobol. In this environment, reducing CPU usage may be a major concern. One option is to use the IDAA as a place to store non-big data objects, perhaps frequently queried tables.

    Common Big Data Health Metrics

    It is best to automate the gathering and reporting of certain statistics that measure certain aspects of your big data environment. These are mostly data-related and are aimed at ensuring that data is complete and consistent. These include the following.

    Cross check table sizes - If you have tables existing in multiple places (such as a Customer table in both native Db2 and in the IDAA), do they have the same number of rows?

    Business rule integrity - Do data elements have values that are correct per the business rules that define them? For example, do all customers have a valid value for Customer-Name? These rules are usually found in the extract, transform and load logic, but may also be found in the code for operational systems.

    Data consistency - Do all data elements have existing, valid values? Consider querying either big data tables or input load files for non-numeric quantities or dates, inter-element consistency (Retire-Date should either be null or be greater than Hire-Date).

    Access path consistency - Is table data accessed using the same Db2 access path every time, or are there exceptions?

    Aggregation consistency - Are there common aggregations (for example sales summarized by region, or shipping costs by product by date), and can they be augmented by pre-aggregating with summary tables?

    Summary

    The health of your big data application is dependent upon how you address both the user experience and resource utilization. Along with regular query capture, analysis and tuning, the DBA should plan on means and methods of archiving old or little-referenced data to reduce I/Os by most queries. Customizing the environment is sometimes possible, perhaps by implementing a stand-alone big data solution, sometimes by extracting data to remote locations for analysis (and consequent reduction in local CPU usage). Finally, metrics exist that can raise flags indicating that your data is becoming less consistent or usable. Consider all the above when supporting your big data solution.


    Thinking About Migrating to Version 11 of DB2 for z/OS? | killexams.com real questions and Pass4sure dumps

    Dec 4, 2013

    Craig S. Mullins

    Version 11 of DB2 for z/OS was released for general availability on Oct. 25, 2013. Even if your company won’t be migrating right away, it is wise to start learning about the new functionality it offers. So let’s take a quick look at some of the highlights of this latest and greatest version of DB2.

    Performance Claims in DB2

    As is normal with a new version of DB2, IBM boasts of performance improvements available in DB2 11. The claims range from out-of-the-box savings ranging from 10% to 40% for different types of query workloads. Your actual savings will vary depending upon things like the query itself, number of columns requests, number of partitions, indexing, and the like. The standard operating procedure of rebinding to achieve the best results still applies. And, of course, if you use the new features of DB2 11 IBM claims that you can achieve even better performance.

    DB2 11 also offers improved synergy with the latest mainframe hardware, the zEC12. For example, FLASH Express and pageable 1MB frames are used for buffer pool control blocks and DB2 executable code. So keep in mind that getting to the latest hardware can help out your DB2 performance and operation!

    Programmer Features in DB2

    In terms of new functionality for developers, DB2 11 offers global variables (for passing data from program to program), improved SQLPL functionality, Alias support for sequence objects, improvements to Declared Global Temporary Tables (DGTTs), views on temporal data, XML improvements (including XQuery support), and a SQL Compatibility feature which can be used to minimize the impact of new version changes on existing applications.

    There is also the new APREUSE(WARN) BIND option, which causes DB2 to try to reuse previous access paths for SQL statements, but does not prevent the bind (or rebind) when access paths cannot be reused.

    DBA Features in DB2

    DB2 11 also offers many new in-depth technical and DBA-related features too. Probably the most important, and one that impacts developers too, is transparent archiving using DB2’s temporal capabilities. If you understand the DB2 10 temporal capabilities, setting up transparent archiving is very similar.

    Another notable feature that will interest many DBAs is the ability to use SQL to query more DB2 Directory tables. And the IBM DB2 Utilities are enhanced with better performance and improved capabilities. For example, REORG offers additional automation, RUNSTATS and LOAD offload more work to zIIP processors, REPAIR offers a new DB2 Catalog repair capability, and DSNACCOX delivers improved performance.

    DB2 11 also delivers improved online schema change functionality, including the long-awaited DROP COLUMN capability, which can be used to clean up unused columns in DB2 tables. Additionally, DB2 11 online schema change supports online altering of limit keys, which enables DBAs to change the limit keys for a partitioned table space without impacting data availability. And DB2 11 also removes some earlier administrative restrictions on administering tables with pending changes.

    Other new DBA capabilities include better control over externalizing Real Time Statistics, better coordination between DB2 and RACF, improved capabilities for column MASKs and PERMISSIONs, 2GB frame size for very large buffer pools, and faster CASTOUT and improved RESTART LIGHT capability for Data Sharing environments.

    Analytics and Big Data Features in DB2

    DB2 11 also boasts new features for supporting big data and analytical processing. Probably the biggest is the ability to support Hadoop access. DB2 11 can be used to enable applications to easily and efficiently access Hadoop data sources using the generic table UDF capability to create a variable shape of UDF output table. Doing so allows access to BigInsights, which is IBM’s Hadoop-based platform for big data. As such, you can use JSON to access Hadoop data via DB2 using the UDF supplied by IBM BigInsights.

    DB2 11 also adds new SQL analytical extensions, including GROUPING SETS, ROLLUP, and CUBE. And a new version (V3) of IBM DB2 Analytics Accelerator (IDAA) is part of the mix too. IDAA V3 brings about improvements such as 1.3 PB of data storage, Change Data Capture support to capture changes to DB2 data and propagate them to IDAA as they happen, additional SQL functions for IDAA queries, and Work Load Manager integration.

    Take Some Time to Learn What DB2 11 Can Do

    DB2 11 for z/OS brings with it a bevy of interesting and useful new features. They range the gamut from development to admin­istration to performance to integration with big data. Now that DB2 11 is out in the field and available for organizations to start using it, the time has come for all DB2 users to take some time to learn what DB2 11 can do. 

    Craig S. Mullins, president and principal consultant with Mullins ?Consulting, Inc., has more than 2 decades of experience in all facets of data management and database systems development. You can reach him via his website at www.craigsmullins.com.


    z/OS® Version 8 DBA Certification Guide: DB2 Environment | killexams.com real questions and Pass4sure dumps

    This chapter is from the book 

    Using DB2's Distributed Data Facility (DDF) provides access to data held by other data management systems or to make your DB2 data accessible to other systems. A DB2 application program can use SQL to access data at other database management systems (DBMSs) other than the DB2 at which the application's plan is bound. This DB2 is known as the local DB2. The local DB2 and the other DBMSs are called application servers. Any application server other than the local DB2 is considered a remote server, and access to its data is a distributed operation.

    DB2 provides two methods of accessing data at remote application servers: DRDA and DB2 private protocol access. For application servers that support the two-phase commit process, both methods allow for updating data at several remote locations within the same unit of work.

    The location name of the DB2 subsystem is defined during DB2 installation. The CDB records the location name and the network address of a remote DBMS. The tables in the CDB are part of the DB2 catalog.

    Distributed Relational Database Architecture

    With DRDA, the recommended method, the application connects to a server at another location and executes packages that have been previously bound at that server. The application uses a CONNECT statement, a three-part name or, if bound with DBPROTOCOL(DRDA), an alias to access the server.

    Queries can originate from any system or application that issues SQL statements as an application requester in the formats required by DRDA. DRDA access supports the execution of dynamic SQL statements and SQL statements that satisfy all the following conditions.

  • The static statements appear in a package bound to an accessible server.

  • The statements are executed using that package.

  • The objects involved in the execution of the statements are at the server where the package is bound. If the server is a DB2 subsystem, three-part names and aliases can be used to refer to another DB2 server.

  • DRDA access can be used in application programs by coding explicit CONNECT statements or by coding three-part names and specifying the DBPROTOCOL(DRDA) bind option. For more on bind options, refer to Chapter 11.

    DRDA access is based on a set of DRDA protocols. (These protocols are documented by the Open Group Technical Standard in DRDA Volume 1: Distributed Relational Database Architecture (DRDA).) DRDA communication conventions are invisible to DB2 applications and allow a DB2 to bind and rebind packages at other servers and to execute the statements in those packages.

    For two-phase commit using SNA connections, DB2 supports both presumed-abort and presumed-nothing protocols that are defined by DRDA. If you are usingTCP/IP, DB2 uses the sync point manager defined in the documentation for DRDA Level 3.

    DB2 Private Protocol

    With private protocol, the application must use an alias or a three-part name to direct the SQL statement to a given location. Private protocol works only between application requesters and servers that are both DB2 for z/OS subsystems.

    A statement is executed using DB2 private protocol access if it refers to objects that are not at the current server and is implicitly or explicitly bound with DBPROTOCOL(PRIVATE). The current server is the DBMS to which an application is actively connected. DB2 private protocol access uses DB2 private connections. The statements that can be executed are SQL INSERT, UPDATE, and DELETE and SELECT statements with their associated SQL OPEN, FETCH, and CLOSE statements.

    In a program running under DB2, a three-part name or an alias can refer to a table or a view at another DB2. The location name identifies the other DB2 to the DB2 application server. A three-part name consists of a location, an authorization ID, and an object name. For example, the name NYSERVER.DB2USER1.TEST refers to a table named DB2USER1.TEST at the server whose location name is NYSERVER.

    Alias names have the same allowable forms as table or view names. The name can refer to a table or a view at the current server or to a table or a view elsewhere. For more on aliases, refer to Chapter 4.

    Private protocol does not support many distributed functions, such as TCP/IP or stored procedures. The newer data types, such as LOB or user-defined types, are also not supported by private protocol. It is not the recommended method to use and is no longer being enhanced or supported from version 8 forward.

    Communications Protocols

    DDF uses TCP/IP or SNA to communicate with other systems. Setting up a network for use by database management systems requires knowledge of both database management and communications. Thus, you must put together a team of people with those skills to plan and implement the network.

    TCP/IP

    Transmission Control Protocol/Internet Protocol (TCP/IP) is a standard communication protocol for network communications. Previous versions of DB2 supported TCP/IP requesters, although additional software and configuration were required. Native TCP/IP eliminates these requirements, allowing gatewayless connectivity to DB2 for systems running UNIX System Services.

    SNA

    System Network Architecture (SNA) is the description of the logical structure, formats, protocols, and operational sequences for transmitting information through and controlling the configuration and operation of the networks. It is one of the two main network architectures used for network communications to the enterprise servers.

    VTAM

    DB2 also uses Virtual Telecommunications Access Method (VTAM) for communicating with remote databases. This is done be assigning two names for the local DB2 subsystem: a location name and a logical unit (LU) name. A location name distinguishes a specific database management system in a network, so applications use this name to direct requests to the local DB2 subsystem. Other systems use different terms for a location name. For example, DB2 Connect calls this the target database name. DB2 uses the DRDA term, RDBNAM, to refer to non-DB2 relational database names.

    Communications Database

    The DB2 catalog includes the communications database (CDB), which contains several tables that hold information about connections with remote systems. These tables are

  • SYSIBM.LOCATIONS

  • SYSIBM.LUNAMES

  • SYSIBM.IPNAMES

  • SYSIBM.MODESELECT

  • SYSIBM.USERNAMES

  • SYSIBM.LULIST

  • SYSIBM.LUMODES

  • Some of these tables must be populated before data can be requested from remote systems. If this DB2 system services only data requests, the CDB does not have to be populated; the default values can be used.

    When sending a request, DB2 uses the LINKNAME column of the SYSIBM.LOCATIONS catalog table to determine which protocol to use.

  • To receive VTAM requests, a LUNAME must be selected in installation panel DSNTIPR.

  • To receive TCP/IP requests, a DRDA port and a resynchronization port must be selected in installation panel DSNTIP5. TCP/IP uses the server's port number to pass network requests to the correct DB2 subsystem. If the value in the LINKNAME column is found in the SYSIBM.IPNAMES table, TCP/IP is used for DRDA connections. If the value is found in the SYSIBM.LUNAMES table, SNA is used.

  • If the same name is in both SYSIBM.LUNAMES and SYSIBM.IPNAMES, TCP/IP is used to connect to the location.

  • A requester cannot use both SNA and TCP/IP to connect to a given location. For example, if SYSIBM.LOCATIONS specifies a LINKNAME of LU1, and if LU1 is defined in both the SYSIBM.IPNAMES and SYSIBM.LUNAMES tables, TCP/IP is the only protocol used to connect to LU1 from this requester for DRDA connections. For private protocol connections, the SNA protocols are used. If private protocol connections are being used, the SYSIBM.LUNAMES table must be defined for the remote location's LUNAME.



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