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000-919 Informix 11.70 System Administrator

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000-919 exam Dumps Source : Informix 11.70 System Administrator

Test Code : 000-919
Test title : Informix 11.70 System Administrator
Vendor title : IBM
exam questions : 123 actual Questions

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IBM Informix 11.70 System Administrator

IBM certified gear Administrator | killexams.com actual Questions and Pass4sure dumps

This seller-selected Certification is offered by course of:IBM CorporationArmonk, the astronomical apple USAPhone: 914-499-1900Email: This e mail address is being blanketed from spambots. You exigency JavaScript enabled to view it.

skill level: Intermediate                          repute: active

low-priced: $200 (shortest song)               

summary:for individuals who administer IBM programs, including, Lotus, IBM set of work, WebSphere, DB2 and Informix Dynamic Server, amongst others.

initial requirements:There are 26 tracks to choose from. Most tracks require you pass one examination, besides the fact that children, some tracks require you hang a system Administrator certification and pass up to a few exams. tests are $200 each. practising is purchasable but not required.

existing tracks include:WebSphere Message broker (v 6.1, 7.0)WebSphere software Server network Deployment (v 6.1, 7.0, eight.0)WebSphere MQ ( v 6.0, 7.0)WebSphere Commerce (v 7.0)WebSphere Portal (6.1, 7.0)AIX (7)DB2 (9, 10) for z/OSInformix Dynamic Server (v11)Informix (11.70)IBM i (6.1)doc ManagerLotus Sametime (eight.0, eight.5)Lotus Notes and Domino (eight, 8.5)Lotus Quickr (8.5) for DominoLotus Quickr (eight.1) for Lotus DominoLotus Quickr (8.1) for WebSphere PortalLotus Connections (2.5)Connections (3.0)

carrying on with requirements:none

Pay Chart:

See sum Ibm Certifications

vendor's web page for this certification


Managing Time collection facts with Informix | killexams.com actual Questions and Pass4sure dumps

Jul 7, 2011

Vaibhav Dantale

Time series facts is a sequence of data points usually measured at successive times and might be spaced at uniform time intervals.  Time-stamped facts can likewise be analyzed to extract significant information or other qualities of the facts.  it could even be used to forecast future movements in accordance with universal previous movements.  Time series facts allows for purposes similar to economic forecasting, census evaluation and forecasting, fleet management, stock market evaluation, and sensible energy metering.

because it is time-stamped, time series data has a separate interior constitution that differs from relational statistics.  additionally, many functions corresponding to sensible metering shop statistics at frequent intervals that require big storage ability.  For these factors, it is not satisfactory to control time series counsel the spend of the simple relational approach of storing one row for every time sequence entry.  Doing so creates efficiency challenges as the information volumes grow exponentially.  Some relational databases tender solutions to wield the performance problem however compromise on storage.  Some non-relational solutions address the storage and performance concerns however endure from obstacles reminiscent of lack of generality, extendibility, and interoperability.

therefore, efficient time series records management requires a solution that reduces storage, ensures towering efficiency, is handy to extend, and interoperates with other relational information and different products.  IBM's Informix TimeSeries feature provides an retort to these complications with breakthrough expertise.

Time series technology has been a confirmed expertise with Informix for 15 years, and with eleven.70,  it comes with the server free of can charge. at first, the time sequence expertise turned into used within the fiscal markets (for time stamped information such as stock ticks). Now, with the modernization of power and utilities trade, with superior metering infrastructures (AMIs), and smart grid initiatives, the time sequence potential is discovering a different opportunity to manipulate the meter or sensor facts for utility agencies.

The Informix TimeSeries feature is a combination of a original time series records class and a huge set of in-build analytics.  It reduces the storage requirement by using greater than 50%, improves efficiency with the aid of orders of magnitude, and improves utility pile productiveness when in comparison to a relational approach.  because the time series information classification is a local facts character in Informix, administrative overhead and researching application is minimal. Informix TimeSeries likewise interoperates well with different relational components and other products similar to Cognos, Streams, and Optim.

major Challenges With a Relational strategy

The natural relational approach outlets one row for anytime series entry resulting in the storage of redundant suggestions.  for instance, smart meter applications could exigency to assemble meter readings every 15 minutes for thousands and thousands of meters.  In a in basic terms relational system a meter_id and timestamp can be kept with each and every meter list.  To enhance retrieval time a composite index on the meter_id column and the timestamp column (desk 1.1) could be required.  This approach results in massive quantities of facts that adds administrative overhead and performance challenges, doubtless requiring further hardware investments.  These challenges commonly become major street blocks for additional enhancements in retort and capabilities.

desk 1.1: illustration of facts saved in ordinary RDBMS method

Meter_id

Timestamp

present

Voltage

Resistance

1

2010-12-01 01:00:00.00000

4

one hundred sixty

40

1

2010-12-01 01:00:10.00000

four.5

155

35

1

2010-12-01 01:00:20.00000

5

one hundred sixty five

33

.

.

.

.

.

.

.

.

2

2010-12-01 01:00:00.00000

four

a hundred seventy five

44

2

2010-12-01 01:00:10.00000

four.5

one hundred sixty

35

.

.

.

.

.

.

.

.

because of the challenges of managing and processing huge information the frequency that statistics is amassed may should be less chummy than favored, for instance, every half hour, in order to slit back the amount of facts it truly is stored.

yet another major challenge is to function time-based mostly analytical operations on relational statistics. many of the time, an utility developer ought to spend complicated and proprietary application profitable judgment to accomplish time-primarily based evaluation.  reasonably frequently these services are not purchasable in the aboriginal SQL language that almost sum databases speak.

The Informix routine to Time series facts

 IBM Informix offers a original point of view with the implementation of time collection as a aboriginal records classification.

The Informix TimeSeries records class makes spend of a solitary row for each tag/tick identifier, reminiscent of a meter, and appends subsequent readings from the equal meter to that row, as shown in table 1.2. The records is ordered physically on disk.  therefore, the variety of rows in a TimeSeries table is a similar because the variety of meters being monitored.  No index is required on the information since it's stored in sorted order.   An index could be created on the meter_id column or some other non-TimeSeries column.  consequently, the storage requirement is decreased via practically 50-eighty% in comparison to a traditional relational approach, and performance is more advantageous by course of an order of magnitude.  here's as a result of not having to create an index on the statistics, not duplicating the Meter_id on every row, and different efficiencies.

table 1.2: representation of records kept in an Informix TimeSeries column

Meter_id

TimeSeries column

1

[(4,160,40), (4.5,155,35)....]

2

[(4,175,44), (4.5,160,35)..]

..

..

sensible metering is an instance where records is stored with at a regular fastened frequency and therefore it is regarded to be an everyday time sequence. however there are determined options the set they deserve to manage counsel for capricious points in time, corresponding to adventure data. Informix helps irregular time series for such circumstances.  Informix supports irregular time sequence just as successfully because it does mediocre time series.

common time collection spend the concept of offset; they absorb got a mapping between the time point linked to an component and its set relative to the delivery of the time sequence. individual timestamps are not saved in common time series; instead, they are computed from the element's offset.  because of this Informix is able to store eleven bytes per checklist in comparison to relational storage.

How does Informix store time sequence suggestions? How is it accessed? How is the frequency of facts assortment defined?  How is incoming statistics validated?

To score the reply for sum these questions, let's look on the Informix time series objects.

Container: A container is an zone created to hang time series records.  The records is stored in the container clustered via identity (as an example meter id) and the sorted by means of time.  dissimilar time-sequence can likewise be saved in a solitary container.  A container is created via executing an SQL command.

Calendar: The calendar defines the frequency of records assortment and times when statistics may noiseless or should not be accrued.  It permits distinctive mixtures of frequencies.  for example, if you exigency to assemble information each day in the week accept Saturday and Sunday, you define the calendar as "5 on, 2 off, day".  The incoming data is validated instantly towards the described calendar.

SQL Routines and APIs: Informix provides over 80 time collection-specific SQL routines to accomplish SQL operations.  It additionally provides a group of C APIs and JAVA APIs to strengthen your personal analytics.  The TimeSeries SQL routines provided operate operations such as developing, aggregating, piteous averages, and arithmetic capabilities on one or more time collection as well as add data to or change information in a time sequence

virtual desk Interface: A view of the time sequence statistics is likewise given that makes time series statistics ascertain fancy in a simple relational schema.  This view is referred to as the digital desk Interface (VTI) and shows time series information in relational structure.  This view makes it possible for universal SQL operations to be performed on the underlying time series records.  note that a VTI table is just a view and does not really withhold any facts at once.  virtual tables may likewise be used in interoperability with different products.

TimeSeries desk

Meter_id

TimeSeries column

1

[(4,160,40), (4.5,155,35)....]

2

[(4,175,44), (4.5,160,35)..]

..

..

virtual desk

Meter_id

Timestamp

current

Voltage

Resistance

1

2010-12-01 01:00:00.00000

four

160

forty

1

2010-12-01 01:00:10.00000

four.5

155

35

1

2010-12-01 01:00:20.00000

5

a hundred sixty five

33

.

.

.

.

.

.

.

.

2

2010-12-01 01:00:00.00000

4

one hundred seventy five

forty four

2

2010-12-01 01:00:10.00000

4.5

a hundred and sixty

35

.

.

.

.

.

.

.

.

 advantages of Informix

much less Storage: due to the miniature index dimension and the selected means of storing the timestamp value, the storage requirement is significantly reduced. Storage discount will likewise be up to 80% in the case of mediocre time collection and as much as 30% in the case of irregular time series.

more desirable efficiency: since the index dimension is miniature and the information is ordered fleshly on disk, an Awful lot less I/O is required to select facts. This effects in extraordinarily excessive efficiency, in each importing and retrieving statistics.  additionally, due to the fact that less disk space is required, administration initiatives fancy backing up and purging statistics are quicker.

This table illustrates the results of an actual customer proof-of-thought comparing Informix towards a different everyday database:

other Database

Informix

Load time for 1,000,000 meters

7 hours

18 minutes

Time to dash required experiences

2 - 7 hours

25 sec to 6 min

Storage required for 1 Million Meters

1.3 TB

350 GB

total pervade of possession: TCO is a worthy deal decrease on the grounds that there is not any further administration, no further license charge, and no lengthy learning curve.  On the contrary, the effects exhibit huge disk zone saving and intensely excessive efficiency.

sooner software development: builders can weigh on latest developed-in SQL routines, C APIs and JAVA APIs for rectify and quicker development.

Interoperability: The Informix TimeSeries statistics type, being a local facts classification, offers interoperability with database points in addition to different products with no further tweaking.

summary

The Informix time collection strategy is a breakthrough know-how for managing and examining time collection statistics, offering different advantages of astronomical reductions on disk storage and very excessive efficiency.  The built-in SQL routines and extensions of C APIs and JAVA APIs allow clients to boost and comprise their personal application common sense into the database engine and improve faster.  since it is convenient to study and use, Informix is being widely approved by course of the utility neighborhood as meeting time series records administration requirements, in comparison with different database and non-RDBMS options.


evaluating the excellent database safety tools | killexams.com actual Questions and Pass4sure dumps

The purpose of database safety gear is to provide more finished protection of relational database administration...

equipment offerings, beyond the safety elements that are integrated into these items. Some of these add-ons bring excessive-conclusion data, evaluation and auditing tools as well. The enchantment of database security gear is that they execute not alter the database or software, and they outcome in barely minimal performance impacts.

this text compares the strengths and weaknesses of a number of database protection tools: database pastime monitoring (DAM), database evaluation and transparent database encryption items. The companies and products addressed listed here (shown in perquisite here desk) are sum enormously rated and leaders within the database protection sector.

Fortinet FortiDB, IBM Guardium, Imperva SecureSphere and Vormetric Inc. are primarily equipment-driven items. The McAfee items (Database exercise Monitoring and Vulnerability manager for Databases), HP safety Voltage, Protegrity united states of america Inc.  and Trustwave DbProtect are primarily software-primarily based items, and Oracle superior safety is an election with Oracle Database enterprise version.

elements

The database recreation monitoring items absorb similar characteristic units: audit coverage compliance (price Card industry records safety usual, medical health insurance Portability and Accountability Act, Gramm-Leach-Bliley Act and so on), transaction blocking off, separation of obligations, centrally managed security, superior reporting and extra.

One differentiating component is the underlying monitoring technology -- how the DAM gathers suggestions -- which is customarily by course of community monitoring, far off monitoring or aboriginal agents. reckoning on a selected vendor's know-how, the enterprise may caution that SQL sniffing performed through community home gear or aboriginal agents offers restrained visibility and can for this understanding leave out some essential recreation. a further may additionally utter that server enter/output, network load and database performance is plagued by agents wanting to cache traffic to the local disk or ship site visitors over the community for analysis. definitely, trendy agents are light-weight and usually absorb an outcome on efficiency by course of below 5%, which is confiscate by trade specifications. however there isn't a legitimate approach to compare the efficiency of a number of DAMs aside from to check them in your own atmosphere.

The types of supported databases is another aspect to believe. Most DAM products can parade screen Oracle, Microsoft SQL Server, IBM DB2, MySQL and Sybase, but some supply back for many extra databases. Imperva SecureSphere adds IBM IMS, IBM Informix, IBM Netezza, MongoDB, PostgreSQL, evolution OpenEdge and Teradata to its list. youngsters, carriers always upgrade their items to be more inclusive and don't sum the time absorb the most existing counsel on their sites. So be confident to request each dealer for a latest listing of supported databases.

Database assessment add-on tools examine database configuration settings and patch stages to find vulnerabilities, and a few integrate with DAM products for alerting and exercise blocking off. assessment add-ons can likewise be essential to database safety because of the depth of inspection and reporting they present, which is often missing in database functions. Fortinet FortiDB, Trustwave DbProtect and Imperva SecureSphere comprehend vulnerability management for databases, whereas IBM Guardium and McAfee sell it as a separate product.

For transparent database encryption, end-to-end coverage, centralized coverage management, scalability and minimal efficiency repercussion are well-known criteria. in this recognize, Vormetric and HP safety Voltage shine. both products are enormously scalable and supply efficient records encryption. Vormetric gives file system and quantity encryption as well as entry manage. Voltage's records-centric security encrypts any contour of facts factor (fee card numbers, individually identifiable information), which contains variable-length strings, numbers, dates, and extra. Vormetric edges out Voltage related to the compass of supported databases and platforms -- Vormetric can encrypt very nearly any category of database on windows, Linux and Unix systems.

Oracle offers table- and column-stage protection, and Protegrity secures records on the software, file, database and column stages.

Ease of deployment and use

equipment-based items, through design, mind to be fairly convenient to deploy. That observed, the extra knotty products, such as IBM Guardium and Imperva SecureSphere, can win weeks to set up and effectively configure.

Fortinet FortiDB home equipment, nonetheless, score towering ratings for simple deployment and setup -- groups can start monitoring a database inside an hour of unpacking the field. The main configuration steps hold specifying an IP address range, making a election on the character of database server to computer screen, identifying a port range, and getting into a username and password. Auto discovery takes it from there.

For the utility-primarily based database recreation monitoring and assessment products, the McAfee products setup is wizard-pushed and extremely handy to configure. The Trustwave DbProtect dashboard, meanwhile, is crisp and neatly-equipped, and the product offers super efficiency charts as well as operational and compliance stories.

setting up transparent database encryption is a fancy technique. Vormetric, Voltage and Protegrity require installation and configuration of a management console and agents. as a result of Oracle superior protection is an election in Oracle Database trade edition, installation is minimal. besides the fact that children, limpid database encryption requires colossal coverage configuration and keystore setup. during this respect, Vormetric, Voltage and Protegrity accomplish spend of graphical person interfaces (GUIs), whereas Oracle configuration is performed at the command-line interface or via a GUI.

As for demo and assessment units, sum the companies let advantage consumers are trying an assessment unit in their personal environment. Fortinet and Vormetric additionally present online demos. related to HP security Voltage, groups should score involved with a revenue rep to request a demo -- unlike the other providers, the election to request a demo isn't simply attainable from the HP site. companies can download a crucible of McAfee Database endeavor Monitoring and McAfee Vulnerability manager for Databases for free.

Pricing

Database protection gear pricing varies vastly, in each dollar quantity and how the product is bought or licensed.

related to database monitoring and evaluation items, Fortinet offers the most straightforward pricing. as an example, Fortinet FortiDB appliances pervade $15,000 to $37,000, and annual upgrade subscriptions and more advantageous encourage add $three,seven hundred to over $9,000 to the cost.

against this, Imperva SecureSphere Database endeavor Monitoring is licensed via database transaction extent, so cost varies based on the atmosphere. With this mannequin, a consumer purchases simplest what's vital and might scale up or down as database activity monitoring wants change. The platform requires a virtual or hardware appliance and administration server; the pervade of a low-end hardware appliance on my own starts around $30,000 and scales as much as over $85,000 for larger-end gadgets.

The enchantment of a database protection tool is that it does not alter the database or utility, and it effects in only minimal performance impacts.

one of the vital products, fancy McAfee Database pastime Monitoring and IBM Guardium, ground pricing on the variety of processor cores. In these circumstances, the corporations prefer advantage clients to contact the vendor or a reseller for selected pricing.

Pricing for limpid encryption is equally diverse. for example, Protegrity Database Protector is likely one of the maximum priced products but is fairly clear-cut. Protegrity licenses its product for a couple of several types of databases. The Protegrity Oracle Database Protector, for example, costs about $17,000 yearly for a two-yr license, or $45,000 for a perpetual license. And the administration console -- commercial enterprise safety Administrator -- costs about $32,000 (two-year time period) to $84,500 (perpetual) for a solitary atmosphere.

In evaluation, Oracle advanced protection pricing is tons extra complicated. The company sells Named person Plus agreements for smaller environments or trade edition per-core licenses for bigger environments. under a Named person Plus settlement, clients exigency to buy 25 licenses per processor, which cost $300 total, plus $sixty six for utility updates, licensing and aid. trade version per-core licensing runs $15,000, plus $3,300 for software updates, licensing and support. noticeably, that you can order Oracle advanced protection licenses without detain from the Oracle site.

aid

all the corporations present regular encourage by the spend of cell, e mail or a client portal, as well as free access to web skills bases. simple assist is typically Monday via Friday sum over enterprise hours with a 4-hour response time. top class assist with 24x7x365 access and quite a lot of levels of response time is accessible, customarily at thousands of greenbacks per kit.

Conclusions

funds is regularly the basic criterion in any protection product, but database protection equipment' deciding to buy metrics compass significantly. identifying components are whether an add-on product has sum imperative required aspects, how it performs in a company's environment, and the course a whole lot application is required to deploy and retain the product.

begin the seller vetting routine with a particular record of facets that your company requires, then check with vendor reps, score contrast devices or crucible application, check the products in-house, and request rectify pricing to your unavoidable ambiance. Then weigh the costs against completeness of characteristic set, ease of spend and efficiency.

Fortinet and McAfee rank excessive on ease of spend and value for database monitoring and evaluation, however they could now not meet sum of a company's necessities. involving transparent database encryption, Vormetric, HP cozy Voltage and Protegrity partake out Oracle advanced safety regarding ease of spend and/or pricing simplicity.

as soon as an organization determines a short listing of items, consider each vendor's sturdiness in the market. The database safety sector has skilled lots of churn over the ultimate two to three years, with some businesses making a couple of strategic purchases and forming partnerships with cloud service providers, while others were scooped up with the aid of the competitors. It can be pattern to preclude companies that are being acquired or are struggling to develop.


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Informix 11.70 System Administrator

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IBM Certified System Administrator | killexams.com actual questions and Pass4sure dumps

This vendor-specific Certification is Offered By:IBM CorporationArmonk, NY USAPhone: 914-499-1900Email: This email address is being protected from spambots. You exigency JavaScript enabled to view it.

Skill Level: Intermediate                          Status: Active

Low Cost: $200 (shortest track)               

Summary:For individuals who administer IBM systems, including, Lotus, IBM Workplace, WebSphere, DB2 and Informix Dynamic Server, among others.

Initial Requirements:There are 26 tracks to choose from. Most tracks require you pass one exam, however, some tracks require you hold a System Administrator certification and pass up to three exams. Exams are $200 each. Training is available but not required.

Current tracks include:WebSphere Message Broker (v 6.1, 7.0)WebSphere Application Server Network Deployment (v 6.1, 7.0, 8.0)WebSphere MQ ( v 6.0, 7.0)WebSphere Commerce (v 7.0)WebSphere Portal (6.1, 7.0)AIX (7)DB2 (9, 10) for z/OSInformix Dynamic Server (v11)Informix (11.70)IBM i (6.1)Document ManagerLotus Sametime (8.0, 8.5)Lotus Notes and Domino (8, 8.5)Lotus Quickr (8.5) for DominoLotus Quickr (8.1) for Lotus DominoLotus Quickr (8.1) for WebSphere PortalLotus Connections (2.5)Connections (3.0)

Continuing Requirements:none

Pay Chart:

See sum Ibm Certifications

Vendor's page for this certification


Shiloh, W2K Advanced Server score solemn Test | killexams.com actual questions and Pass4sure dumps

News

Shiloh, W2K Advanced Server score solemn Test
  • By Scott Bekker
  • October 18, 1999
  • Hardware OEMs are releasing Transaction Processing Performance Council benchmarks based on beta versions of Microsoft Corp.’s SQL Server and Windows 2000 Advanced Server.

    Over the terminal two weeks, Hewlett-Packard Co., Compaq Computer Corp. and Unisys Corp. (www.unisys.com) submitted results to the TPC (www.tpc.org). sum the results were for a original decision back benchmark called the TPC-H, and each came near to the performance of a Sun Microsystems Co.-Informix Corp. result – the only other result posted so far.

    "It would be an understatement to utter that Microsoft is pretty excited about the performance we’ve achieved for this benchmark," says Barry Goffe, a product manager for SQL Server, Microsoft’s flagship relational database management system.

    Officially, each OEM’s submission to the TPC lists the RDBMS as SQL Server 7.5. Goffe says the listing doesn’t constitute an "admission" by Microsoft that SQL Server 7.0’s successor, known by its code title of "Shiloh," will be named SQL Server 7.5. TPC rules don’t permit product code names. Goffe says Microsoft hasn’t finalized what it will summon the RDBMS when it comes out in mid-2000.

    Shiloh just entered its beta testing angle a few weeks ago. About 500 customers and partners are putting the database through its paces. A public beta is planned for early 2000.

    The OEMs ran the benchmarks on eight-way servers based on Intel’s Profusion chipset. The results continue a push by hardware OEMs to prove their prowess with Profusion, the first eight-way chipset that has delivered linear scalability for Windows NT on the Intel platform. Unisys opened the Profusion benchmarking in June by publishing results under the TPC-C, an Online Transaction Processing (OLTP) measure.

    The TPC-H is one of two descendants of the retired TPC-D benchmark, which had measured the performance of decision back database systems. The emergence of a technology known as "materialized views" led to radically improved performance on the TPC-D.

    With a materialized view, a database administrator who knows what data users will query can set up a table that constantly gets that data from other online transactional tables as they are updated.

    Microsoft, which did not back materialized views in SQL Server 7.0 but will provide the feature in Shiloh, and others complained that materialized views robbed the TPC-D benchmark of its value for measuring ad hoc queries.

    The result is two original decision back benchmarks: TPC-H for ad hoc queries and TPC-R for reporting. TPC-R permits the spend of materialized views. So far, only NCR Corp. has published a TPC-R result.

    Sun-Informix posted the first TPC-H result in July: 1,280 queries per hour (QphH) at a cost per QphH of $816 on a Sun Enterprise 4500 system with 12 processors running Informix Dynamic Server AD.

    That ticket was the sole TPC-H result until this month, when the hardware OEMs began publishing their Windows 2000/Profusion/Shiloh results.

    HP was first on Oct. 4 with 1,125 QphH at $253/QphH on a NetServer LXr 8500. Unisys followed Oct. 12 with 1,194 QphH at $288/QphH on an Aquanta ES5085R. On Oct. 14, Compaq delivered 1,233 QphH at $285/QphH on a ProLiant 8500.

    As a group the NT/Intel systems provide 88 percent-96 percent of the performance of the Sun-Informix system at 31 percent-35 percent of the price.

    Compaq, HP and Unisys each listed April 3, 2000 as the availability date for a complete system. -- Scott Bekker

    About the Author

    Scott Bekker is editor in chief of Redmond Channel colleague magazine.


    Managing Time series Data with Informix | killexams.com actual questions and Pass4sure dumps

    Jul 7, 2011

    Vaibhav Dantale

    Time series data is a sequence of data points typically measured at successive times and may be spaced at uniform time intervals.  Time-stamped data can be analyzed to extract meaningful statistics or other characteristics of the data.  It can likewise be used to forecast future events based on known past events.  Time series data enables applications such as economic forecasting, census analysis and forecasting, fleet management, stock market analysis, and smart energy metering.

    Because it is time-stamped, time series data has a special internal structure that differs from relational data.  Additionally, many applications such as smart metering store data at frequent intervals that require massive storage capacity.  For these reasons, it is not adequate to manage time series information using the traditional relational approach of storing one row for each time series entry.  Doing so creates performance challenges as the data volumes grow exponentially.  Some relational databases tender solutions to address the performance issue but compromise on storage.  Some non-relational solutions address the storage and performance issues but suffer from limitations such as lack of generality, extendibility, and interoperability.

    Hence, efficient time series data management requires a solution that reduces storage, ensures towering performance, is light to extend, and interoperates with other relational information and other products.  IBM's Informix TimeSeries feature provides a solution to these problems with breakthrough technology.

    Time series technology has been a proven technology with Informix for 15 years, and with 11.70,  it comes with the server free of charge. Originally, the time series technology was used in the fiscal markets (for time stamped data such as stock ticks). Now, with the modernization of energy and utilities industry, with advanced metering infrastructures (AMIs), and smart grid initiatives, the time series capability is finding a unique opportunity to manage the meter or sensor data for utility companies.

    The Informix TimeSeries feature is a combination of a original time series data character and a big set of in-build analytics.  It reduces the storage requirement by more than 50%, improves performance by orders of magnitude, and improves application evolution productivity when compared to a relational approach.  Because the time series data character is a aboriginal data character in Informix, administrative overhead and learning application is minimal. Informix TimeSeries likewise interoperates well with other relational components and other products such as Cognos, Streams, and Optim.

    Major Challenges With a Relational Approach

    The traditional relational approach stores one row for every time series entry resulting in the storage of redundant information.  For example, smart meter applications may exigency to collect meter readings every 15 minutes for millions of meters.  In a purely relational system a meter_id and timestamp would be stored with each meter record.  To improve retrieval time a composite index on the meter_id column and the timestamp column (Table 1.1) would be required.  This approach leads to massive amounts of data that adds administrative overhead and performance challenges, likely requiring additional hardware investments.  These challenges often become major road blocks for further enhancements in solution and services.

    Table 1.1: Representation of data stored in traditional RDBMS approach

    Meter_id

    Timestamp

    Current

    Voltage

    Resistance

    1

    2010-12-01 01:00:00.00000

    4

    160

    40

    1

    2010-12-01 01:00:10.00000

    4.5

    155

    35

    1

    2010-12-01 01:00:20.00000

    5

    165

    33

    .

    .

    .

    .

    .

    .

    .

    .

    2

    2010-12-01 01:00:00.00000

    4

    175

    44

    2

    2010-12-01 01:00:10.00000

    4.5

    160

    35

    .

    .

    .

    .

    .

    .

    .

    .

    Due to the challenges of managing and processing massive data the frequency that data is collected might exigency to be less frequent than desired, for example, every half hour, in order to reduce the amount of data that is stored.

    Another major challenge is to accomplish time-based analytical operations on relational data. Most of the time, an application developer must spend knotty and proprietary program logic to accomplish time-based analysis.  Quite often these functions are not available in the aboriginal SQL language that most databases speak.

    The Informix Approach to Time series Data

     IBM Informix offers a original perspective with the implementation of time series as a aboriginal data type.

    The Informix TimeSeries data character uses a solitary row for each tag/tick identifier, such as a meter, and appends subsequent readings from the identical meter to that row, as shown in Table 1.2. The data is ordered physically on disk.  Hence, the number of rows in a TimeSeries table is the identical as the number of meters being monitored.  No index is required on the data since it is stored in sorted order.   An index may be created on the meter_id column or any other non-TimeSeries column.  As a result, the storage requirement is reduced by almost 50-80% compared to a traditional relational approach, and performance is improved by an order of magnitude.  This is due to not having to create an index on the data, not duplicating the Meter_id on every row, and other efficiencies.

    Table 1.2: Representation of data stored in an Informix TimeSeries column

    Meter_id

    TimeSeries column

    1

    [(4,160,40), (4.5,155,35)....]

    2

    [(4,175,44), (4.5,160,35)..]

    ..

    ..

    Smart metering is an example where data is stored with at a regular fixed frequency and hence it is considered to be a regular time series. But there are unavoidable solutions where they exigency to manage information for capricious points in time, such as event data. Informix supports irregular time series for such cases.  Informix supports irregular time series just as efficiently as it does regular time series.

    Regular time series spend the concept of offset; they absorb a mapping between the time point associated with an component and its position relative to the start of the time series. Individual timestamps are not stored in regular time series; instead, they are computed from the element's offset.  Because of this Informix is able to redeem 11 bytes per record compared to relational storage.

    How does Informix store time series information? How is it accessed? How is the frequency of data collection defined?  How is incoming data validated?

    To score the retort for sum these questions, let's ascertain at the Informix time series objects.

    Container: A container is a space created to hold time series data.  The data is stored in the container clustered by id (for instance meter id) and the sorted by time.  Multiple time-series can be stored in a solitary container.  A container is created by executing an SQL command.

    Calendar: The calendar defines the frequency of data collection and times when data should or should not be collected.  It allows different combinations of frequencies.  For example, if you want to collect data every day in the week accept Saturday and Sunday, you define the calendar as "{5 on, 2 off}, day".  The incoming data is validated automatically against the defined calendar.

    SQL Routines and APIs: Informix provides over 80 time series-specific SQL routines to accomplish SQL operations.  It likewise provides a set of C APIs and JAVA APIs to develop your own analytics.  The TimeSeries SQL routines provided accomplish operations such as creating, aggregating, piteous averages, and arithmetic functions on one or more time series as well as add data to or change data in a time series

    Virtual Table Interface: A view of the time series data is likewise provided that makes time series data loom to be in a traditional relational schema.  This view is called the Virtual Table Interface (VTI) and shows time series data in relational format.  This view allows regular SQL operations to be performed on the underlying time series data.  Note that a VTI table is just a view and does not actually store any data directly.  Virtual tables can be used in interoperability with other products.

    TimeSeries Table

    Meter_id

    TimeSeries column

    1

    [(4,160,40), (4.5,155,35)....]

    2

    [(4,175,44), (4.5,160,35)..]

    ..

    ..

    Virtual Table

    Meter_id

    Timestamp

    Current

    Voltage

    Resistance

    1

    2010-12-01 01:00:00.00000

    4

    160

    40

    1

    2010-12-01 01:00:10.00000

    4.5

    155

    35

    1

    2010-12-01 01:00:20.00000

    5

    165

    33

    .

    .

    .

    .

    .

    .

    .

    .

    2

    2010-12-01 01:00:00.00000

    4

    175

    44

    2

    2010-12-01 01:00:10.00000

    4.5

    160

    35

    .

    .

    .

    .

    .

    .

    .

    .

     Advantages of Informix

    Less Storage: Due to the miniature index size and the specific course of storing the timestamp value, the storage requirement is drastically reduced. Storage reduction can be up to 80% in the case of regular time series and up to 30% in the case of irregular time series.

    Greater Performance: Because the index size is miniature and the data is ordered physically on disk, much less I/O is required to select data. This results in extremely towering performance, in both uploading and retrieving data.  Also, since less disk space is required, administration tasks fancy backing up and purging data are faster.

    This table illustrates the results of an actual customer proof-of-concept comparing Informix against another well-known database:

    Other Database

    Informix

    Load time for 1,000,000 meters

    7 hours

    18 minutes

    Time to dash required reports

    2 - 7 hours

    25 sec to 6 min

    Storage required for 1 Million Meters

    1.3 TB

    350 GB

    Total Cost of Ownership: TCO is much lower since there is no additional administration, no extra license cost, and no long learning curve.  On the contrary, the results prove huge disk space saving and extremely towering performance.

    Faster application development: Developers can trust on existing built-in SQL routines, C APIs and JAVA APIs for accurate and faster development.

    Interoperability: The Informix TimeSeries data type, being a aboriginal data type, provides interoperability with database features as well as other products with no extra tweaking.

    Summary

    The Informix time series approach is a breakthrough technology for managing and analyzing time series data, offering separate advantages of huge savings on disk storage and extremely towering performance.  The built-in SQL routines and extensions of C APIs and JAVA APIs allow users to develop and incorporate their own program logic into the database engine and develop faster.  Because it is light to learn and use, Informix is being widely accepted by the software community as meeting time series data management requirements, compared with other database and non-RDBMS solutions.



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