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006-002 Certified MySQL 5.0 DBA piece II

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006-002 exam Dumps Source : Certified MySQL 5.0 DBA piece II

Test Code : 006-002
Test appellation : Certified MySQL 5.0 DBA piece II
Vendor appellation : mySQL
: 140 real Questions

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mySQL Certified MySQL 5.0 DBA

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check in to bag MySQL certified on the 2008 MySQL conference & Expo. Certification tests are being offered most efficacious at the conference for this discounted rate of $25 ($175 value). house is limited, most efficacious pre-registered exams are guaranteed a seat on the convention, so badge in now. For answers to often asked questions, search advice from the Certification FAQ.

essential advice examination data
  • exams will be offered Tuesday, Wednesday and Thursday.
  • assessments will be carried out at 10:30 am and at 1:forty pm and should ultimate for 90 minutes.
  • You absorb to be registered as a session or session plus tutorials convention attendee. checks don't appear to be offered to tutorial simplest, note hall most efficacious or conference attendee guest.
  • 10:30am - 12:00pm

  • CMDBA:certified DBA I
  • CMDBA:licensed DBA II
  • CMDEV: certified Developer I
  • CMDEV: certified Developer II
  • CMCDBA: MySQL 5.1 Cluster DBA Certification
  • 1:40pm - 3:10pm

  • CMDBA:certified DBA I
  • CMDBA:licensed DBA II
  • CMDEV: certified Developer I
  • CMDEV: licensed Developer II
  • CMCDBA: MySQL 5.1 Cluster DBA Certification
  • note: a unique exam mp;A Session will be held within the Magnolia Room, Tuesday from 1:00 pm - 1:30 pm

    CMDEV: MySQL 5.0 Developer I & IIThe MySQL 5.0 Developer Certification ensures that the candidate is cognizant of and is in a position to beget exhaust of every of the facets of MySQL that are necessary to develop and hold functions that exhaust MySQL for back-end storage. be cognizant that you simply absorb to travel each of the developer tests (in any order) to acquire certification.

    CMDBA: MySQL 5.0 Database Administrator I & IIThe MySQL Database Administrator Certification attests that the person conserving the certification is cognizant of the route to maintain and optimize an installing of 1 or greater MySQL servers, and function administrative projects akin to monitoring the server, making backups, and so forth. word that youngsters you can moreover Take the CMCDBA examination at any time, you absorb to travel both of the DBA exams (in any order) to obtain certification.

    CMCDBA: MySQL 5.1 Cluster DBA CertificationThe MySQL Cluster Database Administrator certification exam will moreover be administered at the conference. be cognizant that you should attain CMDBA certification before a CMCDBA certification is diagnosed.

    notice: CMDBA and CMCDBA Certification primers are being offered as tutorials perquisite through the MySQL conference & Expo.


    Certification checks are open to convention attendees registered to attend classes. tests aren't available to show-hall handiest individuals or the generic public.


    on-line registration for the checks is attainable. in case you register for the checks along with the conference registration, exam fees can be delivered to your complete convention registration charges. discipline to availability, you can moreover also register and pay for exams on-site. be cognizant that handiest exams paid every through convention registration are guaranteed a seat. Vouchers for checks may be passed to you if you register at the conference and are redeemed at the testing room.

    region and Time

    All exams should be administered in the Magnolia room on the lobby even of the Hyatt Regency Santa Clara (adjoining to the conference center). checks may be provided Tuesday, Wednesday and Thursday. exams will be conducted simplest at 10:30 am and at 1:forty pm and may remaining 90 minutes.


    results of certification tests might be posted outside the trying out room following each examination session and sent to you by means of postal mail immediately following the conference.

    Re-examination policy

    Full conference attendees may moreover pick to re-take any exams now not passed for a $25 payment. There is not any restrict to the variety of instances an exam can be taken. Re-exams are only provided on the conference and may be purchased at the registration desk. most efficacious cash or exams can be authorised onsite.

    Registering for checks

    with a purpose to attend an exam, you ought to convey:

  • charge voucher (acquired on the registration desk)
  • picture identification
  • MySQL Certification Candidate identification quantity. in case you achieve not absorb already got a Certification Candidate identification number from past exams, you should gain one at

  • access MySQL Database With php | real Questions and Pass4sure dumps


    access MySQL Database With Hypertext Preprocessor

    Use the Hypertext Preprocessor extension for MySQL to access statistics from the MySQL database.

  • by means of Deepak Vohra
  • 06/20/2007
  • The MySQL database is essentially the most widely used open supply relational database. It helps distinctive records kinds in these classes: numeric, date and time, and string. The numeric records forms consist of BIT, TINYINT, BOOL, BOOLEAN, INT, INTEGER, BIGINT, DOUBLE, rush and DECIMAL. The date and time information types encompass DATE, DATETIME, TIMESTAMP and 12 months. The string information kinds comprise CHAR, VARCHAR, BINARY, ASCII, UNICODE, text and BLOB. listed here, you're going to learn the route you could entry these information kinds with php scripting language — taking expertise of personal home page 5's extension for the MySQL database.

    set up MySQL DatabaseTo install the MySQL database, you ought to first download the neighborhood version of MySQL 5.0 database for home windows. There are three types: home windows necessities (x86), windows (x86) ZIP/Setup.EXE and with out installer (unzip in C:\). To install the with out installer version, unzip the zip file to a directory. in case you've downloaded the zip file, extract it to a directory. And, in case you've downloaded the home windows (x86) ZIP/Setup.EXE version, extract the zip file to a listing. (See elements.)

    subsequent, double-click on on the Setup.exe utility. you'll spark off the MySQL Server 5.0 Setup wizard. in the wizard, select the Setup classification (the default surroundings is usual), and click on installation to set up MySQL 5.0.

    within the sign-Up body, create a MySQL account, or opt for skip sign-Up. opt for "Configure the MySQL Server now" and click on on conclude. you will set off the MySQL Server illustration Configuration wizard. Set the configuration category to precise Configuration (the default surroundings).

    if you're now not time-honored with MySQL database, choose the default settings in the subsequent frames. via default, server type is set at Developer desktop and database usage is determined at Multifunctional Database. select the drive and listing for the InnoDB tablespace. within the concurrent connections frame, choose the DDSS/OLAP surroundings. subsequent, select the allow TCP/IP Networking and enable Strict Mode settings and exhaust the 3306 port. choose the usual personality Set surroundings and the installation As windows carrier setting with MySQL as the service name.

    within the safety alternatives body, that you can specify a password for the basis consumer (via default, the root user does not require a password). next, uncheck adjust protection Settings and click on Execute to configure a MySQL Server example. eventually, click on on finish.

    if you've downloaded the home windows Installer outfit utility, double-click on the mysql-essential-5.0.x-win32.exe file. you're going to prompt the MySQL Server Startup wizard. comply with the equal procedure as Setup.exe.

    After you absorb got complete installation the MySQL database, log into the database with the MySQL command. In a command instant window, specify this command:

    >mysql -u root

    The default user root will log in. A password isn't required for the default user root:

    >mysql -u <username> -p <password>

    The MySQL command will reveal:


    To listing the database cases in the MySQL database, specify this command:

    mysql>show databases

    by means of default, the watch at various database may be listed. to beget exhaust of this database, specify this command:

    mysql>use verify

    installation MySQL php ExtensionThe php extension for MySQL database is packaged with the personal home page 5 down load (see resources). First, you should set off the MySQL extension within the Hypertext Preprocessor.ini configuration file. bag rid of the ';' before this code line in the file:


    subsequent, restart the Apache2 web server.

    php moreover requires entry to the MySQL client library. The libmysql.dll file is covered with the php 5 distribution. Add libmysql.dll to the home windows outfit course variable. The libmysql.dll file will appear within the C:/php listing, which you delivered to the gadget course if you establish in personal home page 5.

    The MySQL extension offers various configuration directives for connecting with the database. The default connection parameters establish a reference to the MySQL database if a connection isn't designated in a characteristic that requires a connection resource and if a connection has now not already been opened with the database.

    The personal home page class library for MySQL has a variety of capabilities to connect with the database, create database tables and retrieve database records.

    Create a MySQL Database TableNow it be time to create a table within the MySQL database using the php classification library. Create a Hypertext Preprocessor script named createMySQLTable.php in the C:/Apache2/Apache2/htdocs listing. in the script, specify variables for username and password, and connect with the database the usage of the mysql_connect() characteristic. The username root does not require a password. subsequent, specify the server parameter of the mysql_connect() components as localhost:3306:

    $username='root'; $password=''; $connection = mysql_connect ('localhost:3306', $username, $password);

    If a connection is not based, output this oversight message using the mysql_error() function:

    if (!$connection) $e = mysql_error($connection); reverberate "Error in connecting to MySQL Database.".$e;

    you'll deserve to select the database in which a table should be created. opt for the MySQL examine database instance the exhaust of the mysql_select_db() function:

    $selectdb=mysql_select_db('look at various');

    subsequent, specify a SQL observation to create a database desk:

    $sql="CREATE table Catalog (CatalogId VARCHAR(25) primary KEY, Journal VARCHAR(25), writer Varchar(25),edition VARCHAR(25), Title Varchar(seventy five), writer Varchar(25))";

    Run the SQL observation using the mysql_query() function. The connection useful resource that you simply created earlier will be used to dash the SQL statement:

    $createtable=mysql_query ($sql, $connection );

    If a desk isn't created, output this oversight message:

    if (!$createtable) $e = mysql_error($connection); reverberate "Error in developing table.".$e;

    next, add records to the Catalog table. Create a SQL commentary to add facts to the database:

    $sql = "INSERT INTO Catalog VALUES('catalog1', 'Oracle journal', 'Oracle Publishing', 'July-August 2005', 'Tuning Undo Tablespace', 'Kimberly Floss')";

    Run the SQL statement using the mysql_query() feature:

    $addrow=mysql_query ($sql, $connection );

    in a similar fashion, add yet another desk row. exhaust the createMySQLTable.personal home page script proven in record 1. dash this script in Apache net server with this URL: http://localhost/createMySQLTable.php. A MySQL desk will screen (determine 1).

    Retrieve information From MySQL DatabaseYou can retrieve facts from the MySQL database the usage of the personal home page type library for MySQL. Create the retrieveMySQLData.personal home page script in the C:/Apache2/Apache2/htdocs directory. within the script, create a connection with the MySQL database using the mysql_connect() characteristic:

    $username='root'; $password=''; $connection = mysql_connect ('localhost:3306', $username, $password);

    opt for the database from which statistics might be retrieved with the mysql_select_db() formula:

    $selectdb=mysql_select_db('look at various');

    subsequent, specify the choose statement to question the database (The php classification library for MySQL doesn't absorb the supply to bind variables as the php category library for Oracle does.):

    $sql = "opt for * from CATALOG";

    Run the SQL question the usage of the mysql_query() feature:

    $influence=mysql_query($sql , $connection);

    If the SQL query doesn't run, output this oversight message:

    if (!$outcomes) $e = mysql_error($connection); reverberate "Error in running SQL remark.".$e;

    Use the mysql_num_rows() characteristic to achieve the variety of rows in the result aid:


    If the number of rows is improved than 0, create an HTML desk to screen the consequence records. Iterate over the influence set using the mysql_fetch_array() formulation to attain a row of statistics. To achieve an associative array for each and every row, set the result_type parameter to MYSQL_ASSOC:

    while ($row = mysql_fetch_array ($effect, MYSQL_ASSOC))

    Output the row data to an HTML desk the usage of associative dereferencing. for example, the Journal column cost is got with $row['Journal']. The retrieveMySQLData.personal home page script retrieves information from the MySQL database (record 2).

    Run the personal home page script in Apache2 server with this URL: http://localhost/retrieveMySQLData.php. HTML information will appear with statistics bought from the MySQL database (figure 2).

    Now you know a route to exhaust the Hypertext Preprocessor extension for MySQL to entry records from the MySQL database. which you could moreover exhaust the php information Objects (PDO) extension and the MySQL PDO driver to access MySQL with Hypertext Preprocessor .

    concerning the AuthorDeepak Vohra is an internet developer, a solar-certified Java programmer and a solar-certified web piece developer. which you can attain him at

    about the author

    Deepak Vohra, a solar-certified Java programmer and solar-certified internet element developer, has posted a great number of articles in trade publications and journals. Deepak is the author of the engage "Ruby on Rails for personal home page and Java developers."

    MySQL 5.0: To plug or no longer to plug? | real Questions and Pass4sure dumps

    Open supply database dealer MySQL AB has released the most up-to-date edition of its signature database administration device, MySQL 5.0, with original pluggable storage engines -- swappable accessories that proffer the potential so as to add or bag rid of storage engines from a are animated MySQL server. talked to site professional Mike Hillyer to learn the route MySQL purchasers can odds from the brand original pluggable storage engines.

    Hillyer, the webmaster of, a Popular site for individuals who dash MySQL on desirable of windows, currently holds a MySQL knowledgeable Certification and is a MySQL professional at

    What exactly achieve pluggable storage engines deliver to MySQL that wasn't obtainable in ancient types?

    Mike Hillyer: Pluggable storage engines bring the aptitude to add and remove storage engines to a working MySQL server. ahead of the introduction of the pluggable storage engine architecture, users had been required to cease and reconfigure the server when adding and disposing of storage engines. the usage of third-party or in-condo storage engines required additional effort.

    if you had been chatting with a database administrator (DBA) now not established with MySQL, how would you recount the value of the brand original pluggable storage engines?

    Hillyer: Many database management programs exhaust a 'one-measurement-matches-all' approach for information storage -- every table facts is handled the equal manner, in spite of what the records is or the route it is accessed. MySQL took a special approach early on and carried out the thought of storage engines: diverse storage subsystems which are really expert to distinctive exhaust instances.

    MyISAM tables are impeccable to examine massive purposes reminiscent of internet sites. InnoDB supports higher examine/write concurrency. the original Archive storage engine is designed for logging and archival statistics. The NDB storage engine offers very extravagant efficiency and availability.

    One improvement of this design is that their clients had been capable of beget migrating from a legacy device to a SQL DBMS more straightforward by using changing their legacy storage perquisite into a MySQL storage engine, allowing them to challenge SQL queries in opposition t their legacy outfit with out forsaking their ancient techniques.

    Pluggable seems to imply that they are utilized in certain circumstances, or now not at every depending on the administrator's needs. could you define how some of the more essential engines (of the 9) champion a MySQL DBA?

    Hillyer: listed below are a yoke of examples:

    the brand original Archive engine is extraordinary for storing log facts because it makes exhaust of gzip compression and indicates splendid efficiency for inserts and reads with concurrency aid. This skill an administrator can hold on storage and processing costs for logging and archival facts.

    the original Blackhole engine is pleasing in that it takes every INSERT, replace and DELETE statements and drops them; it literally holds no records. That might moreover expose unusual at first, however it works neatly for enabling a replication master to deal with writes with out the exhaust of any storage because the statements nevertheless bag written to the binary log and passed on to the slaves.

    due to the brand original pluggable element, these storage engines can be loaded into the server when mandatory, and unloaded when now not being used.

    Are any of the nine modules anything that has already been piece of database expertise in the past? How does their inclusion in MySQL server beget this app extra robust?

    Hillyer: every one of these storage engines had been in vicinity for reasonably some time, namely MyISAM, InnoDB, BDB, remembrance and MERGE. they are rather ripen and used by using most of their clients. The NDB storage engine is original to MySQL, however is an latest technology that has been in structure for over 10 years.

    The NDB storage engine is an illustration of a storage engine that has contributed to making MySQL extra powerful with the aid of enabling 5 nines of availability when effectively carried out.

    Are there any concerns with MySQL that these pluggable storage engines achieve not handle? How essential is it that additional modules are launched in future types?

    Hillyer: there will always be needs that certain clients absorb that the existing storage engines will now not handle, but the original pluggable approach capacity that it might be increasingly elementary to establish in writing customized storage engines in line with a defined API [application programming interface] and plug them in.

    As these engines are written, it should be enjoyable to watch the innovation that comes from the community, and i watch ahead to trying some of those neighborhood-provided storage engines.

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    Vacancy Details

    Positions in Information Technology Department / Digital Banking Department

    Post Code Post Role / Domain Scale Vacancy 1 Assistant universal Manager System Administrator - AIX, HP-UX, Linux, Windows V 1 2 Chief Manager DBA - Oracle, MySQL, SQL-Server, DB2 IV 2 3 Manager DBA - Oracle, MySQL, SQL-Server, DB2 II 2 4 Chief Manager System Administrator - AIX, HP-UX, Linux, Windows IV 1 5 Manager System Administrator - AIX, HP-UX, Linux, Windows II 2 6 Senior Manager Middleware Administrator - Weblogic, Websphere,JBOSS, Tomcat, Apache, IIS. III 2 7 Chief Manager Application Architect IV 1 8 Manager Application Architect II 1 9 Chief Manager Big Data, Analytics, CRM IV 1 10 Senior Manager Big Data, Analytics, CRM III 1 11 Chief Manager IT Security Specialist IV 1 12 Manager IT Security Specialist II 2 13 Chief Manager Software Testing Specialist IV 1 14 Manager Software Testing Specialist II 2 15 Chief Manager Network Specialist IV 1 16 Senior Manager Network Specialist III 1 17 Manager Virtualisation specialist for VMware, Microsofthypervisor, RHEL(Red Hat Enterprise Linux) II 2 18 Senior Manager Project architect III 1 19 Senior Manager Data Centre Management III 1 20 Manager Network administrator II 2 21 Chief Manager Cyber security specialist IV 1 22 Senior Manager Cyber security specialist III 2 Total 31 Positions in Information Systems Security Cell Post Code Post Role / Domain Scale Vacancy 23 Senior Manager Senior Information Security Manager III 1 24 Manager Information Security Administrators II 3 25 Manager Cyber Forensic Analyst II 1 26 Manager Certified Ethical Hacker &Penetration Tester II 1 27 Assistant Manager Application Security Tester I 1 Total 7 Positions in Treasury Department Post Code Post Role / Domain Scale Vacancy 28 Senior Manager Regulatory Compliance III 1 29 Senior Manager Research Analyst III 1 30 Senior Manager Fixed Income Dealer III 2 31 Manager Equity Dealer II 1 32 Senior Manager Forex Derivative Dealer III 1 33 Senior Manager Forex Global Markets Dealer III 1 34 Manager Forex Dealer II 1 35 Senior Manager Relationship Manager - Trade Finance and Forex III 3 36 Senior Manager Business Research Analyst - Trade Finance and Forex III 1 37 Senior Manager Credit Analyst - Corporates III 1 Total 13 Position in Security Department Post Code Post Role / Domain Scale Vacancy 40 Manager Security Officer II 25 Positions in Credit Post Code Post Role / Domain Scale Vacancy 41 Senior Manager Credit III 20 42 Manager Credit II 30 Total 50 Positions in Planning and evolution Department Post Code Post Role / Domain Scale Vacancy 43 Manager Statistician II 1 44 Assistant Manager Statistician I 1 Total 2 Positions in Premises and Expenditure Department Post Code Post Role / Domain Scale Vacancy 45 Manager Electrical II 2 46 Manager Civil II 2 47 Assistant Manager Civil I 6 48 Assistant Manager Architect I 1 Total 11 RESERVATION SCALE TOTAL SC ST OBC UR OC VI HI ID V 1 0 0 0 1 0 0 0 0 IV 9 2 0 2 5 0 0 0 0 III 42 6 3 11 22 1 0 1 0 II 84 12 6 22 44 0 1 1 1 I 9 1 0 2 6 1 0 0 0 PAY SCALE AND EMOLUMENTS Scale I 23700 980 30560 1145 32850 1310 42020 Scale II 31705 1145 32850 1310 45950 Scale III 42020 1310 48570 1460 51490 Scale IV 50030 1460 55870 1650 59170 Scale V 59170 1650 62470 1800 66070

    Age limit (as on January 1, 2018)

    Post Age Limit Assistant universal Manager 30 to 45 years Manager (All Other) 23 to 35 years Manager (Equity Dealer, Forex Dealer, Risk Management, Security Officer, Credit, Statistician) 25 to 35 years Senior Manager (All Other) 25 to 38 years Senior Manager (Regulatory Compliance, Research Analyst, Fixed Income Dealer, Forex Derivative Dealer, Forex Global Markets Dealer, Relationship Manager - Trade Finance and Forex, commerce Research Analyst - Trade Finance and Forex,Risk Management) 27 to 38 years Chief Manager 27 to 40 years Assistant Manager 20 to 30 years

    Age Relaxation

    Category Age Relaxation SC/ ST 5 years OBC (Non-Creamy Layer) 3 years Ex-Servicemen 5 years Persons ordinarily domiciled in the status of Jammu & Kashmir during the term January 1, 1980 and December 31, 1989 5 years Persons affected by 1984 riots 5 years Qualification

    Educational Qualification (For Post Code 1, 2,3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 and 22):a) 4 year Engineering/ Technology Degree in Computer Science/ Computer Applications/ Information Technology/ Electronics/ Electronics & Telecommunications/ Electronics & Communication/ Electronics & InstrumentationORb) Post Graduate Degree in Electronics/ Electronics & Tele Communication/ Electronics & Communication/ Electronics & Instrumentation/ Computer Science/ Information Technology/ Computer ApplicationsORGraduate having passed DOEACC ‘B’ level

    Post Code Additional Qualification Experience 1 Professional even certification inSystem Administration 10 years sustain in maintenance and Administration of Operating Systems, Databases, Backup Management and Data Centre Management 2 Professional even certification in Database Administration 7 years sustain in maintenance and administration of databases likeOracle/ DB2/ MySql/ SQL Server 3 Associate even certification inDatabase Administration. 3 years sustain in maintenance and administration of databases likeOracle/ DB2/ MySql/ SQL Server. 4 Professional even certification in System Administration 7 years sustain in maintenance andAdministration of Operating Systems. 5 Associate even certification inSystem Administration 3 years sustain in maintenance and Administration of Operating Systems 6 Certification in Middleware Solution 5 years sustain in maintenance andAdministration of Middleware. 7 Certification in Software Development & Programming 7 years sustain in application design, code review and Documentation 8 Certification in Software Development& Programming 7 years sustain in application design, code review and Documentation 9 Certification in mountainous Data/Analytics/ CRM solution 7 years sustain in Analyzing data, uncover information, derive insights and implement data-driven strategies and datamodels in mountainous Data/ Analytic/ CRM technology 10 Certification in mountainous Data/Analytics/ CRM solution 3 years sustain in Analyzing data, uncover information, derive insights and implement data-driven strategies and data models in mountainous Data/Analytic/ CRM technology 11 Certified Information Security Manager/ Certified Information Systems Security Professional 7 years sustain in implementing security improvements by auditing and assessing the current situation; evaluating trends; anticipating requirements and making germane configuration/strategychanges to hold the organization secure. 12 Checkpoint Certified SecurityExpert /CISCO Certified Security Professional. 3 years sustain in implementing security improvements by assessing the current situation; evaluating trends; anticipating requirements and makingchanges to hold the organization secure 13 Certification in software testing. Experience in Software Testing 14 Certification in software testing. Experience in Software Testing 15 Cisco Certified Internetwork Expert (Switching and Routing). 7 years sustain in Routing and switching. Design and implementation of WAN networks. Experience (a) in routing using verge Gateway Protocol(BGP). (b) Drawing up specifications for procurement of Network devices includingrouters, switches, firewalls 16 Cisco Certified InternetworkExpert (Switching and Routing). 5 years sustain in Routing and switching. Design and implementation of WAN networks. Experience in implementation of NetworkAdmission Control (NAC) 17 Associate even CertificationVirtualization Technology. 3 years sustain in Administrationof systems in Virtualized environment 18 Nil 5 years sustain in conceptualizing, esigning and implementation of High-valueorganization even IT projects 19 It is desirable to absorb certificationin Data Centre Management. 5 years sustain in Managing DataCentre Operations. 20 Cisco Certified NetworkProfessional (Routing and Switching) 3 years sustain in Network Troubleshooting,Network Protocols, Routers, Network Administration. 21 Certification in Cyber Security froma recognized institution 7 years sustain Managing Cyber SecurityOperation Centre. 22 Certification in Cyber Security froma recognized institution 5 years sustain Managing Cyber SecurityOperation Centre HOW TO APPLY ONLINE
  • Log on to the official website:
  • Click on "Recruitment to the post"
  • Read the advertisement details very carefully to ensure your eligibility before "Online Application"
  • Click on "Online Application" to fill up the application shape online
  • The candidate would be directed to a page where he/she has to click on "Apply Online" (for the first time registration or original registration)/ already registered candidate just requisite to "Sign In" by using their application number and password sent to their convincing e-mail ID/Mobile No. (This is required always for logging in to their account for shape Submission and Admit Card/Call missive Download)
  • Fill up the application shape as per the guidelines and information sought
  • Candidates requisite to fill up to every required information in "First Screen" tab and click on "SUBMIT" to travel next screen.
  • Fill the every details in the application & upload Photo, Signature.
  • Application fee should be paid through Online & then Submit the Form.
  • Take a print out of online application for future use.

  • Netflix Billing Migration to AWS — piece II | real questions and Pass4sure dumps

    This is a continuation in the sequence on Netflix Billing migration to the Cloud. An overview of the migration project was published earlier here:

    This post details the technical journey for the Billing applications and datastores as they were moved from the Data hub to AWS Cloud.

    As you might absorb read in earlier Netflix Cloud Migration blogs, every of Netflix streaming infrastructure is now completely dash in the Cloud. At the rate Netflix was growing, especially with the imminent Netflix Everywhere launch, they knew they had to travel Billing to the Cloud sooner than later else their existing legacy systems would not be able to scale.

    There was no doubt that it would be a monumental task of touching highly sensitive applications and censorious databases without disrupting the business, while at the same time continuing to build the original commerce functionality and features.

    A few key responsibilities and challenges for Billing:

  • The Billing team is answerable for the financially censorious data in the company. The data they generate on a daily basis for subscription charges, gift cards, credits, chargebacks, etc. is rolled up to finance and is reported into the Netflix accounting. They absorb stringent SLAs on their daily processing to ensure that the revenue gets booked correctly for each day. They cannot tolerate delays in processing pipelines.
  • Billing has zero tolerance for data loss.
  • For most parts, the existing data was structured with a relational model and necessitates exhaust of transactions to ensure an all-or-nothing behavior. In other words they requisite to be ACID for some operations. But they moreover had use-cases where they needed to be highly available across regions with minimal replication latencies.
  • Billing integrates with the DVD commerce of the company, which has a different architecture than the Streaming component, adding to the integration complexity.
  • The Billing team moreover provides data to champion Netflix Customer Service agents to respond any member billing issues or questions. This necessitates providing Customer champion with a comprehensive view of the data.
  • The route the Billing systems were, when they started this project, is shown below.

  • 2 Oracle databases in the Data Center — One storing the customer subscription information and other storing the invoice/payment data.
  • Multiple REST-based applications — Serving calls from the and Customer champion applications. These were essentially doing the CRUD operations
  • 3 Batch applications — Subscription Renewal — A daily job that looks through the customer foundation to determine the customers to be billed that day and the amount to be billed by looking at their subscription plans, discounts, etc.Order & Payment Processor — A sequence of batch jobs that create an invoice to impregnate the customer to be renewed and process the invoice through various stages of the invoice lifecycle.Revenue Reporting — A daily job that looks through billing data and generates reports for the Netflix Finance team to consume.
  • One Billing Proxy application (in the Cloud) — used to route calls from rest of Netflix applications in the Cloud to the Data Center.
  • Weblogic queues with legacy formats being used for communications between processes.
  • The goal was to travel every of this to the Cloud and not absorb any billing applications or databases in the Data Center. every this without disrupting the commerce operations. They had a long route to go!

    The Plan

    We came up with a 3-step blueprint to achieve it:

  • Act I — Launch original countries directly in the Cloud on the billing side while syncing the data back to the Data hub for legacy batch applications to continue to work.
  • Act II — Model the user-facing data, which could live with eventual consistency and does not requisite to be ACID, to persist to Cassandra (Cassandra gave us the aptitude to effect writes in one region and beget it available in the other regions with very low latency. It moreover gives us high-availability across regions).
  • Act III — Finally travel the SQL databases to the Cloud.
  • In each step and for each country migration, learn from it, iterate and help on it to beget it better.

    Act I — Redirect original countries to the Cloud and sync data to the Data Center

    Netflix was going to launch in 6 original countries soon. They decided to Take it as a challenge to launch these countries partly in the Cloud on the billing side. What that meant was the user-facing data and applications would be in the Cloud, but they would silent requisite to sync data back to the Data hub so some of their batch applications which would continue to dash in the Data hub for the time-being, could travail without disruption. The customer for these original countries data would be served out of the Cloud while the batch processing would silent dash out of the Data Center. That was the first step.

    We ported every the APIs from the 2 user-facing applications to a Cloud based application that they wrote using Spring Boot and Spring Integration. With Spring Boot, they were able to quickly jump-start structure a original application, as it provided the infrastructure and plumbing they needed to stand it up out of the box and let us focus on the commerce logic. With Spring Integration they were able to write once and reuse a lot of the workflow style code. moreover with headers and header-based routing champion that it provided, they were able to implement a pub-sub model within the application to establish a message in a channel and absorb every consumers consume it with independent tuning for each consumer. They were now able to ply the API calls for members in the 6 original countries in any AWS region with the data stored in Cassandra. This enabled Billing to be up for these countries even if an entire AWS region went down — the first time they were able to remark the power of being on the Cloud!

    We deployed their application on EC2 instances in AWS in multiple regions. They added a redirection layer in their existing Cloud proxy application to switch billing calls for users in the original countries to recede to the original billing APIs in the Cloud and billing calls for the users in the existing countries to continue to recede to the ancient billing APIs in the Data Center. They opened direct connectivity from one of the AWS regions to the existing Oracle databases in the Data hub and wrote an application to sync the data from Cassandra via SQS in the 3 regions back to this region. They used SQS queues and dead missive Queues (DLQs) to travel the data between regions and process failures.

    New country launches usually carry weight a bump in member base. They knew they had to travel their Subscription Renewal application from the Data hub to the Cloud so that they don’t establish the load on the Data hub one. So for these 6 original countries in the Cloud, they wrote a crawler that went through every the customers in Cassandra daily and came up with the members who were to be charged that day. This every row iterator approach would travail for now for these countries, but they knew it wouldn’t hold ground when they migrated the other countries and especially the US data (which had majority of their members at that time) to the Cloud. But they went ahead with it for now to test the waters. This would be the only batch application that they would dash from the Cloud in this stage.

    We had chosen Cassandra as their data store to be able to write from any region and due to the quick replication of the writes it provides across regions. They defined a data model where they used the customerId as the key for the row and created a set of composite Cassandra columns to enable the relational aspect of the data. The picture below depicts the relationship between these entities and how they represented them in a single column family in Cassandra. Designing them to be a piece of a single column family helped us achieve transactional champion for these related entities.

    We designed their application logic such that they read once at the rise of any operation, updated objects in remembrance and persisted it to a single column family at the recess of the operation. Reading from Cassandra or writing to it in the middle of the operation was deemed an anti-pattern. They wrote their own custom ORM using Astyanax (a Netflix grown and open-sourced Cassandra client) to be able to read/write the domain objects from/to Cassandra.

    We launched in the original countries in the Cloud with this approach and after a yoke of initial minor issues and bug fixes, they stabilized on it. So far so good!

    The Billing system architecture at the recess of Act I was as shown below:

    Act II — Move every applications and migrate existing countries to the cloud

    With Act I done successfully, they started focusing on touching the rest of the apps to the Cloud without touching the databases. Most of the commerce logic resides in the batch applications, which had matured over years and that meant digging into the code for every condition and spending time to rewrite it. They could not simply forklift these to the Cloud as is. They used this chance to remove dead code where they could, demolish out functional parts into their own smaller applications and restructure existing code to scale. These legacy applications were coded to read from config files on disk on startup and exhaust other static resources like reading messages from Weblogic queues — all anti-patterns in the Cloud due to the ephemeral nature of the instances. So they had to re-implement those modules to beget the applications Cloud-ready. They had to change some APIs to supervene an async pattern to allow touching the messages through the queues to the region where they had now opened a secure connection to the Data Center.

    The Cloud Database Engineering (CDE) team setup a multi node Cassandra cluster for their data needs. They knew that the every row Cassandra iterator Renewal solution that they had implemented for renewing customers from earlier 6 countries would not scale once they moved the entire Netflix member billing data to Cassandra. So they designed a system to exhaust Aegisthus to draw the data from Cassandra SSTables and transfigure it to JSON formatted rows that were staged out to S3 buckets. They then wrote Pig scripts to dash mapreduce on the massive dataset everyday to fetch customer list to renew and impregnate for that day. They moreover wrote Sqoop jobs to draw data from Cassandra and Oracle and write to Hive in a queryable format which enabled us to join these two datasets in Hive for faster troubleshooting.

    To enable DVD servers to talk to us in the Cloud, they setup load balancer endpoints (with SSL client certification) for DVD to route calls to us through the Cloud proxy, which for now would pipe the summon back to the Data Center, until they migrated US. Once US data migration was done, they would sever the Cloud to Data hub communication link.

    To validate this huge data migration, they wrote a comparator instrument to compare and validate the data that was migrated to the Cloud, with the existing data in the Data Center. They ran the comparator in an iterative format, where they were able to identify any bugs in the migration, fix them, lucid out the data and re-run. As the runs became clearer and devoid of issues, it increased their self-confidence in the data migration. They were excited to start with the migration of the countries. They chose a country with a little Netflix member foundation as the first country and migrated it to the Cloud with the following steps:

  • Disable the non-GET apis for the country under migration. (This would not repercussion members, but detain any updates to subscriptions in billing)
  • Use Sqoop jobs to bag the data from Oracle to S3 and Hive.
  • Transform it to the Cassandra format using Pig.
  • Insert the records for every members for that country into Cassandra.
  • Enable the non-GET apis to now serve data from the Cloud for the country that was migrated.
  • After validating that everything looked good, they moved to the next country. They then ramped up to migrate set of similar countries together. The ultimate country that they migrated was US, as it held most of their member foundation and moreover had the DVD subscriptions. With that, every of the customer-facing data for Netflix members was now being served through the Cloud. This was a mountainous milestone for us!

    After Act II, they were looking like this:

    Act III — Good bye Data Center!

    Now the only (and most important) thing remaining in the Data hub was the Oracle database. The dataset that remained in Oracle was highly relational and they did not feel it to be a ample conviction to model it to a NoSQL-esque paradigm. It was not workable to structure this data as a single column family as they had done with the customer-facing subscription data. So they evaluated Oracle and Aurora RDS as workable options. Licensing costs for Oracle as a Cloud database and Aurora silent being in Beta didn’t aid beget the case for either of them.

    While the Billing team was sedulous in the first two acts, their Cloud Database Engineering team was working on creating the infrastructure to migrate billing data to MySQL instances on EC2. By the time they started Act III, the database infrastructure pieces were ready, thanks to their help. They had to transfigure their batch application code foundation to be MySQL-compliant since some of the applications used modest jdbc without any ORM. They moreover got rid of a lot of the legacy pl-sql code and rewrote that logic in the application, stripping off dead code when possible.

    Our database architecture now consists of a MySQL master database deployed on EC2 instances in one of the AWS regions. They absorb a calamity Recovery DB that gets replicated from the master and will be promoted to master if the master goes down. And they absorb slaves in the other AWS regions for read only access to applications.

    Our Billing Systems, now completely in the Cloud, watch like this:

    Needless to say, they scholarly a lot from this huge project. They wrote a few tools along the route to aid us debug/troubleshoot and help developer productivity. They got rid of ancient and dead code, cleaned up some of the functionality and improved it wherever possible. They received champion from many other engineering teams within Netflix. They had engineers from the Cloud Database Engineering, Subscriber and Account engineering, Payments engineering, Messaging engineering worked with us on this initiative for anywhere between 2 weeks to a yoke of months. The distinguished thing about the Netflix culture is that everyone has one goal in mind — to deliver a distinguished sustain for their members every over the world. If that means helping Billing solution travel to the Cloud, then everyone is ready to achieve that irrespective of team boundaries!

    The road ahead…

    With Billing in the Cloud, Netflix streaming infrastructure now completely runs in the Cloud. They can scale any Netflix service on demand, achieve predictive scaling based on usage patterns, achieve single-click deployments using Spinnaker and absorb consistent deployment architectures between various Netflix applications. Billing infrastructure can now beget exhaust of every the Netflix platform libraries and frameworks for monitoring and tooling champion in the Cloud. Today they champion billing for over 81 million Netflix members in 190+ countries. They generate and churn through terabytes of data everyday to accomplish billing events. Their road ahead includes rearchitecting membership workflows for a global scale and commerce challenges. As piece of their original architecture, they would be redefining their services to scale natively in the Cloud. With the global launch, they absorb an chance to learn and redefine Billing and Payment methods in newer markets and integrate with many global partners and local payment processors in the regions. They are looking forward to architect more functionality and scale out further.

    If you like to design and implement large-scale distributed systems for censorious data and build automation/tooling for testing it, they absorb a yoke of positions open and would adore to talk to you! Check out the positions here :

    — by Subir Parulekar, Rahul Pilani

    See Also:

    Performance Certification of Couchbase Autonomous Operator on Kubernetes | real questions and Pass4sure dumps

    At Couchbase, they Take performance very seriously, and with the launch of their original product, Couchbase Autonomous Operator 1.0, they wanted to beget certain it’s Enterprise-grade and production ready for customers.

    In this post, they will discuss the minute performance results from running YCSB Performance Benchmark tests on Couchbase Server 5.5 using the Autonomous Operator to deploy on Kubernetes platform. One of the mountainous concerns for Enterprises planning to dash a database on Kubernetes is "performance."

    This document gives a quick comparison of two workloads, namely YCSB A & E with Couchbase Server 5.5 on Kubernetes vs. bare metal.

    YCSB Workload A: This workload has a merge of 50/50 reads and writes. An application case is a session store recording recent actions.

    Workload E: Short ranges: In this workload, short ranges of records are queried, instead of individual records. Application example: threaded conversations, where each scan is for the posts in a given thread (assumed to be clustered by thread id).

    In general, they observed no significant performance degradation in running Couchbase Cluster on Kubernetes, Workload A had on par performance compared to bare metal and Workload E had approximately less than 10% degradation.


    For the setup, Couchbase was installed using the Operator deployment as stated below. For more details on the setup, please advert here.


    Operator deployment: deployment.yaml (See Appendix)

    Couchbase deployment: couchbase-cluster-simple-selector.yaml (See Appendix)

    Client / workload generator deployment: pillowfight-ycsb.yaml (See Appendix) (Official pillowfight docker image from dockerhub and installed java and YCSB manually on top of it)


    7 servers

    24 CPU x 64GB RAM per server

    Couchbase Setup

    4 servers: 2 data nodes, 2 index+query nodes

    40GB RAM quota for data service

    40GB RAM quota for index services

    1 data/bucket replica

    1 primary index replica


    YCSB WorkloadA and WorkloadE

    10M docs

    Workflow after original barren k8s cluster is initialized on 7 servers:

    # allot labels to the nodes so every services/pods will be assigned to perquisite servers:kubectl label nodes arke06-sa09 type=powerkubectl label nodes arke07-sa10 type=clientkubectl label nodes ark08-sa11 type=clientkubectl label nodes arke01-sa04 type=kvkubectl label nodes arke00-sa03 type=kvkubectl label nodes arke02-sa05 type=kvkubectl label nodes arke03-sa06 type=kv #deploy Operator: kubectl create -f deployment.yaml #deploy Couchbase kubectl create -f couchbase-cluster-simple-selector.yaml #deploy Client(s): kubectl create -f pillowfight-ycsb.yaml I ran my tests directly from the client node by logging into the docker image of the client pod: docker exec -it --user root <pillowfight-yscb container id> bash And installing YCSB environment there manually: apt-get upgrade apt-get update apt-get install -y software-properties-common apt-get install python sudo apt-add-repository ppa:webupd8team/java sudo apt-get update sudo apt-get install oracle-java8-installer export JAVA_HOME=/usr/lib/jvm/java-8-oracle cd /opt wget sudo tar -xvzf apache-maven-3.5.4-bin.tar.gz export M2_HOME="/opt/apache-maven-3.5.4" export PATH=$PATH:/opt/apache-maven-3.5.4/bin sudo update-alternatives --install "/usr/bin/mvn" "mvn" "/opt/apache-maven-3.5.4/bin/mvn" 0 sudo update-alternatives --set mvn /opt/apache-maven-3.5.4/bin/mvn git clone

    Running the workloads:

    Examples of YCSB commands used in this exercise: Workload A Load: ./bin/ycsb load couchbase2 -P workloads/workloade -p couchbase.password=password -p -p couchbase.bucket=default -p couchbase.upsert=true -p couchbase.epoll=true -p couchbase.boost=48 -p couchbase.persistTo=0 -p couchbase.replicateTo=0 -p couchbase.sslMode=none -p writeallfields=true -p recordcount=10000000 -threads 50 -p maxexecutiontime=3600 -p operationcount=1000000000 Run: ./bin/ycsb dash couchbase2 -P workloads/workloada -p couchbase.password=password -p -p couchbase.bucket=default -p couchbase.upsert=true -p couchbase.epoll=true -p couchbase.boost=48 -p couchbase.persistTo=0 -p couchbase.replicateTo=0 -p couchbase.sslMode=none -p writeallfields=true -p recordcount=10000000 -threads 50 -p operationcount=1000000000 -p maxexecutiontime=600 -p exportfile=ycsb_workloadA_22vCPU.log

    Test results:

    Env Direct setup Kubernetes pod resources Test Bare metal Kubernetes Delta Env 1 22 vCPU, 48 GB RAM

    (cpu cores and RAM available are set on OS core level)

    Limit to:

    cpu: 22000m = ~22vCPU

    mem: 48GB

    All pods are on dedicated nodes


    50/50 get/upsert

    Throughput: 194,158req/sec

    CPU usage avg: 86% of every 22 cores

    Throughput: 192,190req/sec

    CPU usage avg: 94% of the cpu quota

    – 1% Env 2 16 vCPU, 48 GB RAM

    (cpu cores and RAM available are set on OS core level)

    Limit to:

    cpu: 16000m = ~16vCPU

    mem: 48GB

    All pods are on dedicated nodes


    50/50 get/upsert

    Throughput: 141,909req/sec

    CPU usage avg: 89% of every 16 cores

    Throughput: 145,430req/sec

    CPU usage avg: 100% of the cpu quota

    + 2.5% Workload E: Load: ./bin/ycsb load couchbase2 -P workloads/workloade -p couchbase.password=password -p -p couchbase.bucket=default -p couchbase.upsert=true -p couchbase.epoll=true -p couchbase.boost=48 -p couchbase.persistTo=0 -p couchbase.replicateTo=0 -p couchbase.sslMode=none -p writeallfields=true -p recordcount=10000000 -threads 50 -p maxexecutiontime=3600 -p operationcount=1000000000 Run: ./bin/ycsb dash couchbase2 -P workloads/workloade -p couchbase.password=password -p -p couchbase.bucket=default -p couchbase.upsert=true -p couchbase.epoll=true -p couchbase.boost=48 -p couchbase.persistTo=0 -p couchbase.replicateTo=0 -p couchbase.sslMode=none -p writeallfields=true -p recordcount=10000000 -threads 50 -p operationcount=1000000000 -p maxexecutiontime=600 -p exportfile=ycsb_workloadE_22vCPU.log Env Direct setup Kubernetes pod resources Test Bare metal Kubernetes Delta Env 1 22 vCPU, 48 GB RAM

    (cpu cores and RAM available are set on OS core level)

    Limit to:

    cpu: 22000m = ~22vCPU

    mem: 48GB

    All pods are on dedicated nodes


    95/5 scan/insert

    Throughput: 15,823req/sec

    CPU usage avg: 85% of every 22 cores

    Throughput: 14,281req/sec

    CPU usage avg: 87% of the cpu quota

    – 9.7% Env 2 16 vCPU, 48 GB RAM

    (cpu cores and RAM available are set on OS core level)

    Limit to:

    cpu: 16000m = ~16vCPU

    mem: 48GB

    All pods are on dedicated nodes


    95/5 scan/insert

    Throughput: 13,014req/sec

    CPU usage avg: 91% of every 16 cores

    Throughput: 12,579req/sec

    CPU usage avg: 100% of the cpu quota

    – 3.3% Conclusions

    Couchbase Server 5.5 is production ready to be deployed on Kubernetes with the Autonomous Operator. Performance of Couchbase Server 5.5 on Kubernetes comparable to running on bare metal. There is exiguous performance penalty in running Couchbase Server on Kubernetes platform. Looking at the results Workload A had on par performance compared to bare metal and Workload E had approximately less than 10% degradation.

  • YCSB Workloads
  • Couchbase Kubernetes page
  • Download Couchbase Autonomous Operator
  • Introducing Couchbase Operator
  • Appendix

    My deployment.yaml file:

    apiVersion: extensions/v1beta1 kind: Deployment metadata: name: couchbase-operator spec: replicas: 1 template: metadata: labels: name: couchbase-operator spec: nodeSelector: type: power containers: - name: couchbase-operator image: couchbase/couchbase-operator-internal:1.0.0-292 command: - couchbase-operator # Remove the arguments section if you are installing the CRD manually args: - -create-crd - -enable-upgrades=false env: - name: MY_POD_NAMESPACE valueFrom: fieldRef: fieldPath: metadata.namespace - name: MY_POD_NAME valueFrom: fieldRef: fieldPath: ports: - name: readiness-port containerPort: 8080 readinessProbe: httpGet: path: /readyz port: readiness-port initialDelaySeconds: 3 periodSeconds: 3 failureThreshold: 19

    My couchbase-cluster-simple-selector.yaml file:

    apiVersion: kind: CouchbaseCluster metadata: name: cb-example spec: baseImage: couchbase/server version: enterprise-5.5.0 authSecret: cb-example-auth exposeAdminConsole: true antiAffinity: true exposedFeatures: - xdcr cluster: dataServiceMemoryQuota: 40000 indexServiceMemoryQuota: 40000 searchServiceMemoryQuota: 1000 eventingServiceMemoryQuota: 1024 analyticsServiceMemoryQuota: 1024 indexStorageSetting: memory_optimized autoFailoverTimeout: 120 autoFailoverMaxCount: 3 autoFailoverOnDataDiskIssues: true autoFailoverOnDataDiskIssuesTimePeriod: 120 autoFailoverServerGroup: false buckets: - name: default type: couchbase memoryQuota: 20000 replicas: 1 ioPriority: high evictionPolicy: fullEviction conflictResolution: seqno enableFlush: true enableIndexReplica: false servers: - size: 2 name: data services: - data pod: nodeSelector: type: kv resources: limits: cpu: 22000m memory: 48Gi requests: cpu: 22000m memory: 48Gi - size: 2 name: qi services: - index - query pod: nodeSelector: type: kv resources: limits: cpu: 22000m memory: 48Gi requests: cpu: 22000m memory: 48Gi

    My pillowfight-ycsb.yaml file:

    apiVersion: batch/v1 kind: Job metadata: name: pillowfight spec: template: metadata: name: pillowfight spec: containers: - name: pillowfight image: sequoiatools/pillowfight:v5.0.1 command: ["sh", "-c", "tail -f /dev/null"] restartPolicy: Never nodeSelector: type: client


    kubernetes ,couchbase 5.5 ,database ,performance ,autonomous operator

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