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LOT-920 IBM WebSphere Portal 7.0 progress And(R) Administration

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LOT-920 exam Dumps Source : IBM WebSphere Portal 7.0 progress And(R) Administration

Test Code : LOT-920
Test cognomen : IBM WebSphere Portal 7.0 progress And(R) Administration
Vendor cognomen : IBM
: 112 existent Questions

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IBM IBM WebSphere Portal 7.0

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This chapter is from the e-book 

A provider-Oriented architecture (SOA) is conveniently an IT architectural vogue that permits purposes to be built to support cutting-edge commerce needs of flexibility and integration. Flexibility allows a enterprise to alternate and adapt. Integration emphasizes the communique and interplay of enterprise techniques from conclusion-to-conclusion, both internally and externally with purchasers and suppliers.

IBM WebSphere Portlet manufacturing unit is a fraction of the IBM SOA foundation and supports the "assemble phase" of the SOA life cycle. establishing a SOA software in fact involves creating a service company model and a provider customer mannequin. further SOA elements encompass disconnected guide by way of stub service fashions, computerized carrier checking out, simple service documentation, dynamic provider mapping, and service interface aid.

IBM WebSphere Portal is a component of the IBM SOA basis and supports the "deploy phase" of the SOA life cycle. The installation section comprises a amalgamate of growing the hosting ambiance in your applications and really deploying those functions. IBM WebSphere Portal is a hosting ambiance for the consumer interaction friendly judgment of your SOA application. IBM WebSphere Portal gives you the person interface to SOA. further SOA aspects encompass accessing web functions from portlets, net functions for faraway portlet (WSRP), integrating company processes, and composite functions.

by connecting/integrating an organization's materials including americans, purposes, commerce procedures, and content, IBM WebSphere Portlet manufacturing facility and IBM WebSphere Portal construct portals that give comprehensive interaction and collaboration features.


IBM licensed advanced gadget Administrator | killexams.com existent Questions and Pass4sure dumps

This seller-selected Certification is obtainable by way of:IBM CorporationArmonk, original york USAPhone: 914-499-1900Email: This electronic mail tackle is being protected from spambots. You need JavaScript enabled to view it.

ability stage: superior                          fame: energetic

within your means: $200 (shortest music)               

abstract:For experienced Domino system administrators or equipment administrators original to Domino and who need to plan, deploy, deploy, and exploit Lotus Domino servers and clients, including configuring Domino web servers.

preliminary requirements:You should hold an IBM certified system Administrator - Lotus Notes and Domino certification (for the edition you wish to be certified in) and circulate between one and two additonal exams ($200 each). practising is available but no longer required.

There are currently four tracks to develop a option from: WebSphere Portal (7.0), WebSphere software Server network Deployment (v 6.1) and Lotus Notes and Domino (eight, 8.5).

carrying on with necessities:None specified

Pay Chart:

See every Ibm Certifications

vendor's web page for this certification


FatWire Introduces Free CM Portlets for IBM's WebSphere Portal Server | killexams.com existent Questions and Pass4sure dumps

FatWire utility, a issuer of dynamic content material administration (dCM) and developer of the web application assembly equipment and dynamic content management utility UpdateEngine 6, has added a original dCM Integration package with six free FatWire dCM portlets for IBM's WebSphere Portal. The portlets enable company clients to create and regulate each structured and unstructured content and publish it to the WebSphere Portal to give clients with sparkling, central tips. The dCM Integration equipment and 6 portlets are available at the IBM Portlet Catalog. the brand original dCM Integration package provides endemic J2EE integration between FatWire's dynamic content management application, UpdateEngine, and IBM's internet Sphere Portal v4.1 to enable commerce clients to create, edit, and submit content material to WebSphere Portals. FatWire's six original dCM content-prosperous screen portlets are: the person screen Portlet, for love a glint mapping for portal users to the dCM application; the Launch Pad Portlet, for short access to the complete UpdateEngine interface for extra rigorous CM functionality; the advice Portlet, for personalised display of structured content gadgets similar to advice articles; the Job record Portlet, for quickly content material edits to job listings that open to comprehensive descriptions; the document Portlet, for betray of unstructured content such as MS workplace or pdf files, with arrogate metadata and commentary; and the commercial Portlet, to display ads together with text and pix.

(http://www.fatwire.com), (http://www.ibm.com)


LOT-920 IBM WebSphere Portal 7.0 progress And(R) Administration

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LOT-920 exam Dumps Source : IBM WebSphere Portal 7.0 progress And(R) Administration

Test Code : LOT-920
Test cognomen : IBM WebSphere Portal 7.0 progress And(R) Administration
Vendor cognomen : IBM
: 112 existent Questions

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IBM WebSphere Portal 7.0 progress And(R) Administration

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Implementing Retries with a MDB or an MQ Batch Job? (WAS 7, MQ 6) | killexams.com existent questions and Pass4sure dumps

We need to listen for messages distributed via Websphere MQ to regain informed when an employee joins or leaves IBM. And because the resources used in the processing (a database, a webservice) may be temporarily unavailable, they must be able to deal with such outages, which may sweep from minutes to hours, by repeatedly retrying the processing after some delay. And they must be also able to deal with “poison messages”, that means messages whose processing always fails either because their content is invalid or because their data isn’t consistent with the database.

The question is whether this would be better implemented as a Message-Driven Bean (MDB) or a batch job regularly checking its queue given that they love Websphere Application Server 7 (and thus Java EE 5) and Websphere MQ 6, which both love some notable changes compared to the previous versions. It turns out that it depends – both approaches love some advantages and disadvantages and so it’s a question of the likelihood of particular problems and commerce requirements and priorities.

Setting the scene MDB vs. a batch job: the determination factors

Whether they should select the MDB or the batch job approach depends on a number of factors, some of them are:

  • Requirements
  • Quantity: What quantity of messages enact they need to handle?
  • Error likelihood: What’s the probability that a resource will be temporarily unavailable or that a message will accommodate data that can’t be processed correctly and how soon such a problem needs to be resolved? I.e. can they wait to another day or shall they regain going as soon as the resource is up again? This will recount us how often they need to retry and whether a manual handling of an issue is sufficient.
  • Support for mistake handling/retrial logic
  • Ease of use/development/maintenance
  • Performance: They need to handle every the incoming messages and to love minimal negative repercussion on the  performance of the target system
  • Speed of processing of the incoming messages (immediate vs. once or few times per day)
  • Integration with their operations monitoring (logging, their Operations Dashboard webapp)
  • The problems to deal with

    There are three types of problems that can occur:

  • A failure to communicate with MQ, for instance because a network connection got interrupted
  • Inability to process a message due to a resource (a DB or a WS) being temporary unavailable
  • A poison (invalid) message (wrong data type, unexpected content) leading to an exception during its processing
  • The two approaches Approach 1: A Message-Driven Bean (MDB)

    A MDB is hosted by an application server that does a lot of work on behalf of the bean (such as transaction and concurrency management) thus simplifying its progress and configuration. It may be as simple as writing

    @javax.ejb.MessageDrivenpublic class SimpleMessageBean implements javax.jms.MessageListener { public void onMessage(javax.jms.Message inMessage) { final javax.jms.TextMessage msg = (javax.jms.TextMessage) inMessage; final String msgBody = msg.getText(); // handle the msgBody ... }}

    and configuring the ActivationSpecification for the MDB in JNDI via the app. server’s administration UI.

    The question is, of course, how well it can handle poison messages and retrial when resources are temporarily unavailable.

    MDB mistake handling and configuration in Websphere 7

    Let’s love a recognize how Websphere deals with various kinds of errors related to MDBs and how they enact configure a MDB in this application server, especially with esteem to mistake handling.

    MDB mistake handling in Websphere

    What happens when an mistake occurs?

    Normally an Application Server starts an MQ transaction before it invokes a MDB and it either commits it when the MDB finishes or rolls it back when it throws an exception. If the transaction succeeds then the message is removed from the MDB’s queue otherwise it will be returned there and processed again in the future. This is the default behavior corresponding to configuring container-managed transactions (tx) with the type of ‘required’. Notice that also DB operations can participate in this transaction and thus be committed/rolled back as well, which might be useful.

  • In the case of an MQ communication/connection failure, WAS logs the exception and retries the connection later based on its configuration. It’s also viable to set an ExceptionListener that would be called with the exception as a parameter in such a case.
  • In the case of an exception during message processing (or due to a manual setRollbackOnly invocation) the current transaction is rolled back, the message is attach back to the queue and the MDB is restarted. When the queue is re-checked, the message is found again and passed to another MDB. If the antecedent of the problem persists, this will fail again – and so on.
  • We love two ways how to deal with a failed message:

  • Remove the message from the queue either by discarding it or by pitiable it to the queue’s “back-out queue”. This is arrogate when the message itself is the problem (e.g. contains data uncongenial with the DB …).
  • Stop processing messages from the queue (pause the Activation Specification) and restart it later when the problem is resolved. This is arrogate when a necessary resource is temporarily unavailable.
  • Messaging provider and JMS resources configuration related to mistake handling

    We will employ JCA 1.5 Activation Specification (and not Listener Ports that are deprecated since WAS 7) with Websphere MQ as the provider, which limits their configuration options to those described below.

  • Disabling (temporarily) the whole queue, more exactly shutting down the MDB
  • “Number of sequential delivery failures before suspending endpoint” – on an MQ Activation Specification
  • “Stop endpoint if message delivery fails” – if true, message delivery suspended when the Number of sequential delivery failures… exceeded
  • Removing problematic messages (this is done by Websphere MQ itself, not WAS)
  • “Backout threshold” (BOTHRESH; a property of a queue, configured via MQ) specifies the maximum number of times a message can be attach onto a queue before it is moved to the specified backout requeue queue.  Default: 0 or unset?! => never re-delivered
  • “Backout requeue queue” (BOQNAME; a property of a queue, configured via MQ) – the queue where to attach the failed messages; default: SYSTEM.DEAD.LETTER.QUEUE
  • WARNING: This seems to apply only to a queue, not to a topic. But underneath topics employ (likely dynamic) queues anyway so it should be viable somehow.
  • Other related settings
  • Interesting resources:

    Design of the MDB approach Error handling design

    The main problem with the MDB approach is that it doesn’t support retrying an operation after a slow (either for a single failing message or for the whole queue, if a resource is temporarily unavailable). There are some workarounds, but not very nice.

  • For a single message I couldn’t find a way to implement retrials after some, preferably increasing, delay; the only thing they can enact is to retry it few times with the default Websphere’s delay, which seems to be 5s, and if it still doesn’t succeed then scurry it into a special queue that would be processed manually while perhaps also sending an email notification.
  • If there is some global problem, such as an unavailable resource, indicated by several consecutive failures of one or more messages (depending on the content of the queue), they could let WAS stop the MDB and re-enable it later either automatically after a slow or manually when the problem gets fixed.
  • MDB design
  • When resource unavailability is detected, let WAS stop the MDB automatically via the setting “Number of sequential delivery failures before suspending endpoint”. It will need to be re-enabled either manually or automatically.
  • Manual re-activation of the MDB: They love to anyway detect that the MDB was disabled (the only option is perhaps by watching the log), find out why it failed, and re-enable it via the Websphere Administration Console.
  • Automated re-activation: Implement a scheduled stateless EJB, which re-enables the MDB after few tens of minutes – preferably enact this few times with increasing delay, if still failing, give up and notify an admin.
  • When there is a poison message, scurry it to the backout queue and notify somebody to handle it (e.g. via email)
  • If the queue contains only one message there is no generic way how to find out whether the problem is within the message or in some resource, the MDB would need to find this out and communicate it. If there are multiple messages and only one fails, they know it’s a poison message and it could be automatically removed by means of the “Backout threshold”. (Beware of the interaction between the message’s redelivery count/backout threashold and the “Number of sequential delivery failures…” – the letter is reset when either a message processing succeeds or when the MDB is stopped/restarted.)
  • (Perhaps they could employ JMS selectors on JMS header properties (e.g. JMSRedeliveredto, JMSXDeliveryCount) but the possibilities are rather limited because both the selector query and the properties are static (e.g. something love MyRetryTime >= now() isn’t possible). Note: MQ V7 has a major rewrite of the selectors support and their handling was moved from the Java client directly to the queue manager.)
  • MDB approach evaluation Key MDB issues
  • Permissions to accomplish a WAS administration operation required.
  • Difficult to distinguish a poison message from a resource outage without additional logic when the queue contains only one element.
  • But behold the batch job design below, which also requires to be able to distinguish these two types of problems.
  • Inefficient determination of MDB’s status for the slow reactivation logic: either polling its status regularly or watching the log with many unrelated messages that can’t be filtered out.
  • Key MDB advantages and disadvantages
  • Advantages
  • The data is processed and reaches the destination system soon after it is published
  • Key characteristics are configurable via UI (Number of sequential delivery failures, Backout threshold, MQ connection data, MQ security/SSL, processing concurrency, DataSource configuration/injection, …). Actually this is also a handicap due to needing an admin, behold below
  • Logging configurable at the runtime (Java logging, levels can be set in WAS console)
  • Disadvantages
  • Any configuration requires a WAS administrator and thus lot of time due to the IBM bureaucracy and ceremony
  • Difficult to collect and communicate statistics for their Operations Dashboard because (a) there are frequent fine-grained changes instead of 1/day batch changes and (b) there is no support for the Job logging framework of ours (a viable but laborious solution is to gather statistics in an instance variable and log them in regular intervals into the job tables using JDBC and some code extracted from the job framework)
  • Necessary to anyway configure the reactivation EJB (the reactivation delay, number of attempts before giving up)
  • MDB design questions:

  • Do they need automated reactivation of a disabled MDB? Perhaps not if: (1) a resource outage happens rarely and/or (2) the administration team spots this automatically and can handle it automatically without any bureaucracy and consumption of their resources.
  • MDB resources

    Essential docs

    Other (not every docs available for their version, namely MQ v6 and WAs v7)

    Approach 2: A batch job checking MQ regularly

    A batch job is a command-line application that is regularly, for specimen once a day, flee by cron and actively scans its incoming queue/topic for original messages and processes them every at once. every the JMS communication and management and configuration must be implemented from scratch. (Though utilities such as Spring JMS template may simplify it.)

    Job mistake handling and configuration Error handling

    The problems and ways to deal with errors are the very as when running in an application server, only they love to enact everything ourselves. That means they need to manually start a transaction, ensnare exception and commit/roll back and configure the topic/queue for poison messages.

    We would need to implement a problem antecedent detection logic to distinguish whether there is a temporary resource outage or whether there is a problem with the message itself (either incorrect data type or data uncongenial with the target DB ). There is no other friendly way to deal with these separate kinds of problems without really knowing which of them it is.

    We would deal with the problems as follows:

  • For a resource outage, retry few times with an increasing delay, then quit and postpone the processing till the next scheduled execution
  • For a poison message, scurry it to the backout queue and notify an administrator
  • JMS configuration in a batch job

    We love two ways to configure the JMS resources (a Topic and a (Topic)ConnectionFactory) and their options related to mistake handling:

  • Use MQ provider-specific APIs to create the objects and configure them. behold this JMS + MQ API example.
  • Configure the provider-specific resources in JNDI and employ only the standardized JNDI and JMS APIs. This is very facile with Sun’s filesystem-based JNDI provider (fscontext.jar and providerutil.jar) and vendor-supplied tools for generating the JNDI .bindings file for existing JMS resources . In the case of MQ you can enact it in the MQ Explorer GUI or with the command-line utility JMSAdmin (a JMSAdmin example, another one).
  • You can create the JNDI configuration via the MQ Explorer wizards – after having added a original JNDI “context” using fscontext and a local directory – either by first creating the JMS resource and then letting the wizard generate an MQ resources for it and adjusting it as needed:

    Or by creating the JMS resource from an existing MQ resource:

    Provided that the FsContext configuration file .bindings produced by JMSAdmin/MQ Explorer is in the folder /etc/mqJndiconfig, they would connect to the MQ as follows:

    final Hashtable<String, String> env = original Hashtable<String, String>();env.put(Context.INITIAL_CONTEXT_FACTORY, "com.sun.jndi.fscontext.RefFSContextFactory");env.put(Context.PROVIDER_URL, "file:/etc/mqJndiconfig");final InitialContext context = original InitialContext(env);ConnectionFactory qcf = (javax.jms.ConnectionFactory) context.lookup("MyConnectionFactory"); // Note: I set the channel property MCAUSER so it actually isn't necessary to supply credentials below:final Connection connection = qcf.createConnection("anna", "password ignored");// Client ID is necessary for a durable subscr.// They could alternatively set in on the ConnectionFactory - the CLIENTID propertyconnection.setClientID("MyCoolApplication");final Session session = connection.createSession(true, -1); // the param 2 is ignored for durable subscr.final Topic destination = (Topic) context.lookup(JNDI_PREFIX + TOPIC);final MessageConsumer receiver = subscribe(session, destination);try {connection.start();} ensnare (javax.jms.JMSException e) {throw original RuntimeException("Failed to start the JMS connection", e);}

    We would then read the messages via:

    while ((msg= receiver.receiveNoWait()) != null) {handleMessage(msg);}

    The dependencies comprise jms.jar, fscontext.jar and providerutil.jar. You can find them either in the WMQ installation or on the web.

    You may want to love a recognize at Writing a simple publish/subscribe application connecting through WebSphere MQ in WMQ help, which discusses some of the code above in more detail.

    Job design
  • Set a reasonable backout threshold and a suitable backout queue on the queue used by the Topic so that problematic messages are removed automatically after few failed attempts
  • Some monitoring of the backout queue would be necessary. If the MQ infrastructure doesn’t provide it then they can implement another MQ/JMS reader that would route an email when there are some original messages in the queue.
  • Regarding the type of the topic queue:
  • Either they can employ the shared JMS queue (SYSTEM.JMS.D.SUBSCRIBER.QUEUE) for the topic
  • Or they can employ a non-shared queue unique for their application, which would be actually better and more aligned with IBM standards. It’s achieved by setting a broker durable subscription queue pattern in the contour “SYSTEM.JMS.D..*” (notice the trailing *) on the JMS ConnectionFactory when defining it in JNDI or in the Java code. Upon the first connection a permanent dynamic queue is generated for the client. They can then set the backout options on it (or the administrators may define a model queue for these dynamic queues with this setting already applied).
  • Read and process each message in a original MQ transaction so that if the processing fails it will be attach back into the queue (and its delivery count will be increased, thus making it perhaps eligible for the backout queue)
  • Batch job approach evaluation
  • Advantages
  • Simple implementation offlexibledelayed retrials – upon a resource outage, discontinuance the job and try again during the next scheduled flee or, perhaps, retry first after a manual slow (Thread.sleep(); beware connection timeouts).
  • Simple integration into their monitoring/logging framework incl. the Operations Dashboard.
  • Disadvantages
  • More coding to set up/clean the resources and handle errors, which is not trivial, and thus also more bug prone.
  • Concurrent processing of the messages would be considerably more difficult to implement correctly if viable at every (if MQ JMS does implement the necessary optional methods). They would need to employ the advanced methods targeted at app. server vendors – there is a non-MQ specimen of a multithreaded (non-durable subscription) consumer. Hopefully it could be modified for a durable one using Connection.createDurableConnectionConsumer with the very simple implementation of ServerSessionPool.
  • Impl. details: The “pool” would always create a original custom ServerSession implementation. instance, whose getSession() would simply create a original transacted TopicSession, set its MessageListener, and flee the session in a original Thread when start() called. Notice that (Topic)Session implements Runnable, whose run() invokes the provided listener sequentially for available messages. The listener would process a message and summon commit/rollback on its owning session (see this transactional listener example).
  • Important: Handling of failed messages would need to be considered carefully as returning a message to the queue would lead to its immediate re-processing and likely rejection by one of the other threads, exceeding its backout treshold in a few seconds and thus subverting the delayed retrial processing. On the other hand, as mentioned above, they should anyway be able to distinguish resource outage, in which case they would stop processing immediately, and a problematic message, which would anyway discontinuance up in the backout queue so this is perhaps not a existent issue.
  • Note: When using MessageListeners, it’s notable to set an ExceptionListener on the connection because some errors can only be communicated this way.
  • Summary and conclusion

    The version and fixpack flush of WMQ/WAS is very important.

    Both the approaches love some pros and cons and it depends on the requirements and their priority which one would be more suitable.

    MDB: It’s more difficult to implement delayed retrial if it is required – it may be implemented via a scheduled EJB automatically re-enabling the MDB stopped by WAS after a number of failures (one issue is that we’d need WAS admin rights for the EJB to enact that; another is performance due to the need to either monitor logs or check the MDB’s status regularly). On the other hand, concurrent processing is available out of the box and also implementing a bean notifying about problematic messages in the backout queue is simpler thanks to the injection of the mail API resources. This solution may thus require some JMX and Java EE (scheduled EJB) magic and there may be unexpected problems with that.

    JOB: Concurrency: it’s more difficult to implement processing of the messages in parallel, there is even a slight haphazard that it’s impossible. Also  more coding is required and thus there will be more bugs. On the other hand they can implement delayed retrials as they want. Thus if concurrent processing isn’t censorious while the automatic delayed retrial may be then this would be the best approach.

     

    From http://theholyjava.wordpress.com/2010/09/13/implementing-retrial-with-a-mdb-or-an-mq-batch-job-was-7-mq-6/


    Inside the IBM BigInsights platform for Big data management | killexams.com existent questions and Pass4sure dumps

    Editor's note: In June 2017, IBM announced that it is ending the progress of BigInsights and becoming a reseller of Hortonworks Inc.'s Hadoop distribution, Hortonworks Data Platform (HDP). As fraction of the deal, IBM will work to migrate every existing IBM BigInsights customers to HDP.

    IBM BigInsights combines its enterprise capabilities and industry-standard Hadoop components into a single platform, enabling users to manage and analyze large volumes of structured and unstructured data.

    IBM BigInsights features several advanced analytics capabilities, including sophisticated text analytics; BigSheets for advanced data exploration; and Big SQL, which enables SQL access to data in a Hadoop cluster. Added-value enterprise capabilities are designed to enhance and simplify application progress and system implementation, as well as provide features that ameliorate performance, scalability, reliability, security and administration.

    IBM BigInsights release 4.1 includes the IBM Open Platform with Apache Hadoop, as well as several prepackaged value-add modules containing proprietary advanced enterprise-grade features.

    IBM Open Platform with Apache Hadoop, IBM's core distribution of open source Hadoop, includes the following Apache components: Ambari (2.1), Apache Kafka (0.8.2), Flume (1.5.2),Ganglia (3.1.7), Hadoop ( 2.7.1), HBase (1.1.1), Hive (1.2.1), Knox (0.6.0), Lucene (4.7.0), Nagios (3.5.1), Oozie (4.2.0), Parquet (4.0), Parquet MR/format (1.6.0/2.2), Pig (0.15.0), Slider (0.80.0), Solr (5.1.0), Spark (1.4.1), Sqoop (1.4.6.), Terada Connector for Hadoop (1.4) and Zookeeper (3.4.6)

    BigInsight value-add modules include:

    IBM BigInsights Analyst, which provides specific tools for data analysis. The modules comprise BigInsights Home service, the primary interface used to launch other BigInsights components, as well as Big SQL and BigSheets:

  • Big SQL is an advanced SQL engine that provides users who love standard SQL query skills with love a glint query access to data in a Hadoop cluster within a single query, whether it be in Hive, HBase or Hadoop Distributed File System enabled by massively parallel processing technology. The product also supports federated query access to IBM DB2, Oracle, Teradata and Open Database Connectivity sources.
  • BigSheets lets users explore, transform and accomplish visualizations on large data sets stored in Hadoop through a spreadsheet-like Web interface. The tool supports love a glint queries against massive data sets by translating user actions into MapReduce functions against the Hadoop cluster.
  • IBM BigInsights Data Scientist, which enables users with advanced analytics skills tools to gain further insight into the data in the cluster. In addition to components provided as fraction of the Analyst module, the following tools are also included:

  • Big R, which provides users chummy with the R language a set of libraries, enabling them to develop and employ R language functions on data residing in the IBM BigInsights cluster. This tool lets users accomplish complicated operations and queries using R against large data sets by hiding some of the complexity of writing MapReduce functions.
  • Text Analytics, which is a powerful and intuitive tool for extracting information from unstructured and semi-structured text.
  • SystemML, which provides users with a tool to employ an R-like syntax to accomplish statistical functions and machine learning constructs. The tools enable the algorithms to be executed in a distributed vogue across nodes of a cluster using MapReduce or Spark (in memory). IBM contributed SystemML to the open source community, and it has been accepted as an Apache Incubator project.
  • IBM Enterprise Management module, which provides enterprise-grade capabilities to support cluster scaling and performance through parallel computing and application grid management. The module also provides other enterprise features to support cluster security and reliability. IBM Enterprise Management includes IBM Spectrum Scale-FPO, a Portable Operating System Interface-compliant file system that can be used in set of Hadoop Distributed File System. This gives administrators more control and improved integration capabilities with other systems in the enterprise. also included is IBM Platform Symphony, which provides administrators with tools to efficiently manage multiple platform instances as well as enables support for data isolation for multi-tenant environments.

    IBM BigInsights for Apache Hadoop, which includes the contents of the three modules illustrious above.

    BigInsights modules operate on Linux servers. minute system requirements comprise operating system and hardware, as well as supported software.

    While IBM BigInsights modules can be downloaded and installed on-premises, the company also offers BigInsights on Cloud, Hadoop as a service on IBM's global cloud infrastructure. This option provides users with every the features of BigInsights in a 24/7 managed environment.

    IBM BigInsights licensing and distribution

    While IBM's Open Platform with Apache Hadoop is available as an open source free-to-use distribution, BigInsight's value-add modules require IBM licensing for purposes other than evaluation. Contact IBM or an IBM commerce partner for minute pricing and support options.

    IBM offers the BigInsights Quick Start evaluation edition of its software for nonproduction use.

    IBM is a founding member of the Open Data Platform Initiative, a group of Big data industry leaders and vendors that promote technologies based on open source on the Apache Hadoop ecosystem and share in efforts to promote interoperability of Big data tools.


    An Extreme Makeover | killexams.com existent questions and Pass4sure dumps

    To provide technical assistance and developmental lore to fight poverty and disease, the World Bank first had to overhaul its antiquated I.T. system and build a global network.

    An Extreme Makeover

    Before Muhsin and the ISG group, which numbered more than 400 by 1998, could provide the necessary support for the four Strategic Partnership Programs (decentralization, lore sharing, renewal of bank I.T. and implementation of cost effectiveness) that he had spelled out in the September 1997 bank newsletter, he and his team had to rebuild the bank's infrastructure from the ground up. "Obviously, they had to immaculate this mess up," Denning says. "If they cleaned it up, we'd be more efficient as a lending organization. But they really needed to regain their lore in the hands of their partners [government, non-government and private-sector organizations, etc.]. Only then could they solve the world's problems with poverty."

    In 1997, the bank selected SAP R/3 4.0B (it later migrated to the 4.6C version) as its primary engine for I.T. improvement. With the SAP ERP system, the bank replaced disparate administrative systems and created a unified I.T. environment so that the very commerce processes could be used in Washington and in the 100 or so field offices. Eight SAP components—SAP Financials, SAP Fund Management, SAP Controlling, SAP Materials Management, SAP Project Management, SAP Project System, SAP Human Resources-Travel Management and SAP Enterprise Buyer—were brought in to streamline procurement, materials management, project systems and fiscal reporting.

    The bank originally budgeted $43 million for the SAP ERP suite, according to internal bank documents, but the project soon was $10 million over budget. In a narrative that appeared in a number of publications, including the Harvard commerce Review and CIO magazine, Wolfensohn was upset by the overrun and summoned Muhsin to his office to explain. Muhsin, in turn, brought in Ken Thornton, then general manager of IBM's global public sector practice, to address Wolfensohn's concerns. The bank president had a long-standing friendship with IBM's then-CEO, Lou Gerstner, and IBM had been brought in as a strategic partner on the ERP implementation.

    After Thornton explained to Wolfensohn that 80% of every ERP implementations ran over budget, Wolfensohn made it lucid he wanted the bank to be fraction of that 20% minority. Thornton pleaded with Wolfensohn not to lose faith and urged him "not to blink." Later, when Muhsin ran into the bank president in the elevator, Wolfensohn assured him he wasn't going to blink. He was as friendly as his word. According to internal bank documents, he got the bank's board to sanction the additional $10 million, and ultimately project costs came to $54.3 million.

    In the end, Wolfensohn clearly made the prerogative decision. With the SAP ERP system, which was completed in 18 months, the bank consolidated its legacy systems and databases, while reducing cycle time with electronic approval of projects. "For us at the World Bank, the SAP implementation was a very Big deal," Muhsin said in a SAP advice release.

    The SAP ERP project only represented fraction of the bank's I.T., process and communications overhaul. "We used SAP for every commerce transactions and brought in Oracle for databases," says Ronald Kim, information officer for the World Bank Institute (WBI). The WBI serves as the bank's capacity progress arm, helping countries share and apply global and local lore to meet progress challenges.

    Specifically, Oracle is being used as the foundation for the bank's Record Integrated Information System. This is the repository for every of the bank's official records, reports, e-mails, and audio and video. With Oracle, the bank was seeking database scalability—a key factor in dealing with a large population of users around the world—as well as availability, performance and security. With Oracle's InterMedia database feature, it can also store and manage multimedia data.

    In 2002, the bank began soliciting RFPs for a solution that would enable it to better organize and retrieve the millions of documents, many of them going back almost 60 years and written in dozens of languages, stored within its global repository. In effect, this would serve as the commerce intelligence solution for the bank's global lore sharing system. The vendor chosen—Teragram, a multi-lingual, natural-language technology company based in Cambridge, Mass.—makes categorization software that is used in high-demand environments such as large Internet search engines (Yahoo), major advice companies (The original York Times), and numerous Fortune 500 companies and fiscal organizations. The bank chose Teragram's TK240 Version 5, the company's flagship taxonomy management software (software that automatically analyzes document contents and classifies and categorizes them). Typically, bank employees transmit documents to a document management system that uses the Oracle database. Each of these documents is read by the TK240 software, which applies linguistic-based identification to each document and then assigns meta-data tags based on predetermined indicators.

    "Teragram was able to create a system that worked across multiple languages for better categorization, storage and quick retrieval," says Yves Schabes, who co-founded Teragram. "The biggest challenge in a large organization is to be able to find information stored in many environments and many offices and many languages. The larger the organization, the more of an issue this is."

    The bank also built its own management dashboard, which enables management to access SAP and Oracle data on the Web and update key commerce metrics. It brought in Lotus Notes as its e-mail and collaboration tool, and a repository of documents in Lotus Notes databases, according to the WBI's Kim. IBM's Domino.doc, a commercial IBM Lotus product, was acquired primarily for content storage.

    Web technology, which the bank characterizes as "the interface of option for lore sharing," was also critical. birth in 2003, the bank began what it called the Internet Services Program (ISP), a multi-year project to upgrade its Internet capacities. To support this, it acquired IBM WebSphere Servers and WebSphere Portal Servers; Netegrity Web security software; iPlanet Directory Server; and Vignette content management software.

    For online collaboration, it uses Lotus Sametime, a commercial product that provides collaborative tools and workspaces. Google is used to retrieve information from the bank's internal and external Web sites, while Epublish, a home-built Web publishing tool based on the Vignette content management software, is used for content caching.

    Next Page: The Ouagadougou Factor



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    References :


    Dropmark : http://killexams.dropmark.com/367904/11723116
    Wordpress : http://wp.me/p7SJ6L-1j6
    Issu : https://issuu.com/trutrainers/docs/lot-920
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    publitas.com : https://view.publitas.com/trutrainers-inc/never-miss-these-lot-920-questions-before-you-go-for-test
    zoho.com : https://docs.zoho.com/file/5xjzy907b5301be7a4df78f3b3f5de1212186






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