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

Test Code : 006-002
Test designation : Certified MySQL 5.0 DBA fraction II
Vendor designation : mySQL
: 140 existent Questions

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mySQL Certified MySQL 5.0 DBA

Get MySQL certified | killexams.com existent Questions and Pass4sure dumps

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

essential advice examination data
  • exams will breathe offered Tuesday, Wednesday and Thursday.
  • assessments will breathe carried out at 10:30 am and at 1:forty pm and should ultimate for 90 minutes.
  • You breathe pleased to breathe registered as a session or session plus tutorials convention attendee. checks don't seem to breathe offered to tutorial simplest, expose hall most effectual 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 breathe 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 vigilant of and is in a position to contour expend of every bit of of the facets of MySQL that are necessary to develop and preserve functions that expend MySQL for back-end storage. breathe vigilant that you simply breathe pleased to scurry 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 vigilant of the artery to maintain and optimize an installing of 1 or greater MySQL servers, and office administrative projects akin to monitoring the server, making backups, and so forth. word that youngsters you can likewise engage the CMCDBA examination at any time, you breathe pleased to scurry 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 likewise breathe administered at the conference. breathe vigilant that you should attain CMDBA certification before a CMCDBA certification is diagnosed.

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

    Eligibility

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

    payment

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

    region and Time

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

    consequences

    results of certification tests might breathe 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 likewise 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 breathe taken. Re-exams are only provided on the conference and may breathe purchased at the registration desk. most effectual cash or exams can breathe 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 consequence not breathe pleased already got a Certification Candidate identification number from past exams, you should gain one at mysql.com/certification/signup.

  • access MySQL Database With php | killexams.com existent Questions and Pass4sure dumps

    In-Depth

    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, flow 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 artery 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, pick the default settings in the subsequent frames. via default, server kind 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, pick the DDSS/OLAP surroundings. subsequent, select the allow TCP/IP Networking and enable Strict Mode settings and expend the 3306 port. pick the customary 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 apparatus 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 breathe pleased 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:

    mysql>

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

    mysql>show databases

    by means of default, the see at various database may breathe listed. to contour expend 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. entangle rid of the ';' before this code line in the file:

    extension=php_mysql.dll

    subsequent, restart the Apache2 web server.

    php likewise 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 apparatus course variable. The libmysql.dll file will seem within the C:/php listing, which you delivered to the gadget course if you allocate 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 breathe 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 mistake message using the mysql_error() function:

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

    you'll deserve to select the database in which a table should breathe created. opt for the MySQL examine database instance the expend 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 breathe used to rush the SQL statement:

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

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

    if (!$createtable) $e = mysql_error($connection); echo "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. expend the createMySQLTable.personal home page script proven in record 1. rush 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 kind 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 breathe retrieved with the mysql_select_db() formula:

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

    subsequent, specify the pick statement to question the database (The php classification library for MySQL doesn't breathe pleased 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 mistake message:

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

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

    $nrows=mysql_num_rows($result);

    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 charge 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 seem with statistics bought from the MySQL database (figure 2).

    Now you know a artery to expend the Hypertext Preprocessor extension for MySQL to entry records from the MySQL database. which you could likewise expend 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 fraction developer. which you can attain him at dvohra09@yahoo.com.

    about the author

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


    MySQL 5.0: To plug or no longer to plug? | killexams.com existent 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 tender the potential so as to add or entangle rid of storage engines from a are live MySQL server.

    SearchOpenSource.com talked to site professional Mike Hillyer to learn the artery MySQL purchasers can advantage from the brand original pluggable storage engines.

    Hillyer, the webmaster of VBMySQL.com, a well-liked site for individuals who rush MySQL on desirable of windows, currently holds a MySQL knowledgeable Certification and is a MySQL professional at consultants-change.com.

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

    Mike Hillyer: Pluggable storage engines bring the ability 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 portray the value of the brand original pluggable storage engines?

    Hillyer: Many database management programs expend a 'one-measurement-matches-all' approach for information storage -- every bit of table facts is handled the equal manner, in spite of what the records is or the artery 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 expend instances.

    MyISAM tables are faultless to examine weighty 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 extreme efficiency and availability.

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

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

    Hillyer: listed below are a brace of examples:

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

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

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

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

    Hillyer: every one of these storage engines had been in vicinity for reasonably some time, namely MyISAM, InnoDB, BDB, recollection and MERGE. they are rather develope 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 pile 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 consequence not handle? How essential is it that additional modules are launched in future types?

    Hillyer: there will always breathe needs that distinct clients breathe pleased that the existing storage engines will now not handle, but the original pluggable approach capacity that it might breathe increasingly elementary to allocate 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 breathe enjoyable to see the innovation that comes from the community, and i see ahead to trying some of those neighborhood-provided storage engines.


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    Certified MySQL 5.0 DBA fraction II

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    Indian Bank Recruitment 2018: Apply online for 145 Specialist Officer posts | killexams.com existent questions and Pass4sure dumps

    NEW DELHI: The Indian Bank, a leading Public Sector Bank, has invited applications for the Specialist Officer SO Posts of coadjutant general Manager, coadjutant Manager, Manager, Senior Manager, & Other Posts.

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    Vacancy Details

    Positions in Information Technology Department / Digital Banking Department

    Post Code Post Role / Domain Scale Vacancy 1 Assistant general 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 development 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 circumscribe (as on January 1, 2018)

    Post Age Limit Assistant general 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 state of Jammu & Kashmir during the period 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 level certification inSystem Administration 10 years undergo in maintenance and Administration of Operating Systems, Databases, Backup Management and Data Centre Management 2 Professional level certification in Database Administration 7 years undergo in maintenance and administration of databases likeOracle/ DB2/ MySql/ SQL Server 3 Associate level certification inDatabase Administration. 3 years undergo in maintenance and administration of databases likeOracle/ DB2/ MySql/ SQL Server. 4 Professional level certification in System Administration 7 years undergo in maintenance andAdministration of Operating Systems. 5 Associate level certification inSystem Administration 3 years undergo in maintenance and Administration of Operating Systems 6 Certification in Middleware Solution 5 years undergo in maintenance andAdministration of Middleware. 7 Certification in Software Development & Programming 7 years undergo in application design, code review and Documentation 8 Certification in Software Development& Programming 7 years undergo in application design, code review and Documentation 9 Certification in astronomical Data/Analytics/ CRM solution 7 years undergo in Analyzing data, uncover information, derive insights and implement data-driven strategies and datamodels in astronomical Data/ Analytic/ CRM technology 10 Certification in astronomical Data/Analytics/ CRM solution 3 years undergo in Analyzing data, uncover information, derive insights and implement data-driven strategies and data models in astronomical Data/Analytic/ CRM technology 11 Certified Information Security Manager/ Certified Information Systems Security Professional 7 years undergo in implementing security improvements by auditing and assessing the current situation; evaluating trends; anticipating requirements and making germane configuration/strategychanges to preserve the organization secure. 12 Checkpoint Certified SecurityExpert /CISCO Certified Security Professional. 3 years undergo in implementing security improvements by assessing the current situation; evaluating trends; anticipating requirements and makingchanges to preserve 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 undergo in Routing and switching. Design and implementation of WAN networks. Experience (a) in routing using rim Gateway Protocol(BGP). (b) Drawing up specifications for procurement of Network devices includingrouters, switches, firewalls 16 Cisco Certified InternetworkExpert (Switching and Routing). 5 years undergo in Routing and switching. Design and implementation of WAN networks. Experience in implementation of NetworkAdmission Control (NAC) 17 Associate level CertificationVirtualization Technology. 3 years undergo in Administrationof systems in Virtualized environment 18 Nil 5 years undergo in conceptualizing, esigning and implementation of High-valueorganization level IT projects 19 It is desirable to breathe pleased certificationin Data Centre Management. 5 years undergo in Managing DataCentre Operations. 20 Cisco Certified NetworkProfessional (Routing and Switching) 3 years undergo in Network Troubleshooting,Network Protocols, Routers, Network Administration. 21 Certification in Cyber Security froma recognized institution 7 years undergo Managing Cyber SecurityOperation Centre. 22 Certification in Cyber Security froma recognized institution 5 years undergo Managing Cyber SecurityOperation Centre HOW TO APPLY ONLINE
  • Log on to the official website: indianbank.in/
  • 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 contour online
  • The candidate would breathe 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 necessity to "Sign In" by using their application number and password sent to their sound e-mail ID/Mobile No. (This is required always for logging in to their account for contour Submission and Admit Card/Call letter Download)
  • Fill up the application contour as per the guidelines and information sought
  • Candidates necessity to fill up to every bit of required information in "First Screen" tab and click on "SUBMIT" to scurry next screen.
  • Fill the every bit of details in the application & upload Photo, Signature.
  • Application fee should breathe paid through Online & then Submit the Form.
  • Take a print out of online application for future use.

  • Netflix Billing Migration to AWS — fraction II | killexams.com existent questions and Pass4sure dumps

    This is a continuation in the train 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 focus to AWS Cloud.

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

    There was no doubt that it would breathe a monumental job of moving highly sensitive applications and faultfinding databases without disrupting the business, while at the very time continuing to build the original commerce functionality and features.

    A few key responsibilities and challenges for Billing:

  • The Billing team is responsible for the financially faultfinding 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 breathe pleased 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 expend of transactions to ensure an all-or-nothing behavior. In other words they necessity to breathe ACID for some operations. But they likewise had use-cases where they needed to breathe 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 likewise provides data to uphold Netflix Customer Service agents to retort any member billing issues or questions. This necessitates providing Customer uphold with a comprehensive view of the data.
  • The artery 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 www.netflix.com and Customer uphold applications. These were essentially doing the CRUD operations
  • 3 Batch applications — Subscription Renewal — A daily job that looks through the customer base to determine the customers to breathe billed that day and the amount to breathe billed by looking at their subscription plans, discounts, etc.Order & Payment Processor — A train of batch jobs that create an invoice to impregnate the customer to breathe 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 relaxation 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 scurry every bit of of this to the Cloud and not breathe pleased any billing applications or databases in the Data Center. every bit of this without disrupting the commerce operations. They had a long artery to go!

    The Plan

    We came up with a 3-step scheme to consequence it:

  • Act I — Launch original countries directly in the Cloud on the billing side while syncing the data back to the Data focus for legacy batch applications to continue to work.
  • Act II — Model the user-facing data, which could live with eventual consistency and does not necessity to breathe ACID, to persist to Cassandra (Cassandra gave us the ability to accomplish writes in one region and contour it available in the other regions with very low latency. It likewise gives us high-availability across regions).
  • Act III — Finally scurry the SQL databases to the Cloud.
  • In each step and for each country migration, learn from it, iterate and ameliorate on it to contour 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 engage 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 breathe in the Cloud, but they would quiet necessity to sync data back to the Data focus so some of their batch applications which would continue to rush in the Data focus for the time-being, could work without disruption. The customer for these original countries data would breathe served out of the Cloud while the batch processing would quiet rush out of the Data Center. That was the first step.

    We ported every bit of 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 pile 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. likewise with headers and header-based routing uphold that it provided, they were able to implement a pub-sub model within the application to allocate a message in a channel and breathe pleased every bit of consumers consume it with independent tuning for each consumer. They were now able to handle the API calls for members in the 6 original countries in any AWS region with the data stored in Cassandra. This enabled Billing to breathe up for these countries even if an entire AWS region went down — the first time they were able to see 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 depart to the original billing APIs in the Cloud and billing calls for the users in the existing countries to continue to depart to the former billing APIs in the Data Center. They opened direct connectivity from one of the AWS regions to the existing Oracle databases in the Data focus 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 extinct letter Queues (DLQs) to scurry the data between regions and process failures.

    New country launches usually express a bump in member base. They knew they had to scurry their Subscription Renewal application from the Data focus to the Cloud so that they don’t allocate the load on the Data focus one. So for these 6 original countries in the Cloud, they wrote a crawler that went through every bit of the customers in Cassandra daily and came up with the members who were to breathe charged that day. This every bit of row iterator approach would work 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 breathe the only batch application that they would rush from the Cloud in this stage.

    We had chosen Cassandra as their data store to breathe able to write from any region and due to the fleet 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 lone column family in Cassandra. Designing them to breathe a fraction of a lone column family helped us achieve transactional uphold for these related entities.

    We designed their application logic such that they read once at the genesis of any operation, updated objects in recollection and persisted it to a lone column family at the sojourn 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 breathe 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 brace of initial minor issues and bug fixes, they stabilized on it. So far so good!

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

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

    With Act I done successfully, they started focusing on moving the relaxation of the apps to the Cloud without moving 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 opening to remove extinct code where they could, rupture 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 expend other static resources dote 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 contour the applications Cloud-ready. They had to change some APIs to ensue an async pattern to allow moving 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 bit of 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 expend Aegisthus to tug the data from Cassandra SSTables and transform it to JSON formatted rows that were staged out to S3 buckets. They then wrote Pig scripts to rush mapreduce on the massive dataset everyday to fetch customer list to renew and impregnate for that day. They likewise wrote Sqoop jobs to tug data from Cassandra and Oracle and write to Hive in a queryable format which enabled us to associate 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 call back to the Data Center, until they migrated US. Once US data migration was done, they would sever the Cloud to Data focus communication link.

    To validate this huge data migration, they wrote a comparator appliance 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 aplomb in the data migration. They were excited to start with the migration of the countries. They chose a country with a diminutive Netflix member base 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 impact members, but retard any updates to subscriptions in billing)
  • Use Sqoop jobs to entangle the data from Oracle to S3 and Hive.
  • Transform it to the Cassandra format using Pig.
  • Insert the records for every bit of 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 eventual country that they migrated was US, as it held most of their member base and likewise had the DVD subscriptions. With that, every bit of of the customer-facing data for Netflix members was now being served through the Cloud. This was a astronomical milestone for us!

    After Act II, they were looking dote this:

    Act III — Good bye Data Center!

    Now the only (and most important) thing remaining in the Data focus was the Oracle database. The dataset that remained in Oracle was highly relational and they did not feel it to breathe a dependable credence to model it to a NoSQL-esque paradigm. It was not feasible to structure this data as a lone column family as they had done with the customer-facing subscription data. So they evaluated Oracle and Aurora RDS as feasible options. Licensing costs for Oracle as a Cloud database and Aurora quiet being in Beta didn’t uphold contour 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 transform their batch application code base to breathe MySQL-compliant since some of the applications used modest jdbc without any ORM. They likewise got rid of a lot of the legacy pl-sql code and rewrote that logic in the application, stripping off extinct code when possible.

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

    Our Billing Systems, now completely in the Cloud, see dote this:

    Needless to say, they scholarly a lot from this huge project. They wrote a few tools along the artery to uphold us debug/troubleshoot and ameliorate developer productivity. They got rid of former and extinct code, cleaned up some of the functionality and improved it wherever possible. They received uphold 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 brace of months. The worthy thing about the Netflix culture is that everyone has one goal in mind — to deliver a worthy undergo for their members every bit of over the world. If that means helping Billing solution scurry to the Cloud, then everyone is ready to consequence 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, consequence predictive scaling based on usage patterns, consequence single-click deployments using Spinnaker and breathe pleased consistent deployment architectures between various Netflix applications. Billing infrastructure can now contour expend of every bit of the Netflix platform libraries and frameworks for monitoring and tooling uphold in the Cloud. Today they uphold 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 fraction of their original architecture, they would breathe redefining their services to scale natively in the Cloud. With the global launch, they breathe pleased an opening 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 dote to design and implement large-scale distributed systems for faultfinding data and build automation/tooling for testing it, they breathe pleased a brace of positions open and would worship to talk to you! Check out the positions here :

    — by Subir Parulekar, Rahul Pilani

    See Also:

    Performance Certification of Couchbase Autonomous Operator on Kubernetes | killexams.com existent questions and Pass4sure dumps

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

    In this post, they will contend 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 astronomical concerns for Enterprises planning to rush 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 mix 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 breathe 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.

    Setup

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

    Files

    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)

    Hardware

    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

    Tests

    YCSB WorkloadA and WorkloadE

    10M docs

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

    # allocate labels to the nodes so every bit of services/pods will breathe assigned to birthright 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 http://download.nextag.com/apache/maven/maven-3/3.5.4/binaries/apache-maven-3.5.4-bin.tar.gz 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 http://github.com/couchbaselabs/YCSB

    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 couchbase.host=10.44.0.2 -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 rush couchbase2 -P workloads/workloada -p couchbase.password=password -p couchbase.host=10.44.0.2 -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

    WorkloadA

    50/50 get/upsert

    Throughput: 194,158req/sec

    CPU usage avg: 86% of every bit of 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

    WorkloadA

    50/50 get/upsert

    Throughput: 141,909req/sec

    CPU usage avg: 89% of every bit of 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 couchbase.host=10.44.0.2 -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 rush couchbase2 -P workloads/workloade -p couchbase.password=password -p couchbase.host=10.44.0.2 -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

    WorkloadE

    95/5 scan/insert

    Throughput: 15,823req/sec

    CPU usage avg: 85% of every bit of 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

    WorkloadE

    95/5 scan/insert

    Throughput: 13,014req/sec

    CPU usage avg: 91% of every bit of 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 breathe deployed on Kubernetes with the Autonomous Operator. Performance of Couchbase Server 5.5 on Kubernetes comparable to running on bare metal. There is diminutive 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.

    References
  • YCSB Workloads https://github.com/brianfrankcooper/YCSB/wiki/Core-Workloads
  • Couchbase Kubernetes page https://www.couchbase.com/products/cloud/kubernetes
  • Download Couchbase Autonomous Operator https://www.couchbase.com/downloads
  • Introducing Couchbase Operator https://blog.couchbase.com/couchbase-autonomous-operator-1-0-for-kubernetes-and-openshift/
  • 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: metadata.name 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: couchbase.database.couchbase.com/v1 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

    Topics:

    kubernetes ,couchbase 5.5 ,database ,performance ,autonomous operator



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