Training command

6. How do you see command line history in UNIX? Very useful indeed, use history command along with grep command in UNIX to find any relevant command you have already executed. Purpose of this Unix Command Interview Questions is probably to check how familiar candidate is from available tools in UNIX operation system. 7. How do you copy file from one host to other? Many options but you can say by using "scp" command. You can also use rsync command to answer this UNIX interview question or even sftp would be ok. 8. How do you find which process is taking how much CPU? By using "top" command in UNIX, there could be multiple follow-up UNIX command interview questions based upon response of this because “TOP” command has various interactive options to sort result based upon various parameter. Read more: http://javarevisited.blogspot.com/2011/05/unix-command-interview-questions.html#ixzz3W1KOcqlC

UNIX Interview Questions and Answers UNIX or Linux operating system has become default Server operating system and for whichever programming job you give interview you find some UNIX command interview questions there. These UNIX command interview questions are mostly asked during Java development and Support role interviews on various investment banks mostly because most of electronic trading systems or stock trading system works on Unix servers. As we know that high volume low latency systems which wants to take advantage of little bit of volatility in market for Equity , Futures and options or Foreign exchange trading need a stable server side operating system and Redhat Linux is doing great job there. with the advent of Algorithmic trading this speed factor becomes more important so getting someone who has good knowledge of operating system and commands on which these trading system runs is definitely required. but these UNIX command interview questions are equally applicable for any job interview which requires some work on Unix Operating System. With the growing use of Linux in form of RedHat, Solaris and IBM AIX its must to keep you familiar with essential Linux commands available on various platforms. Unix and Linux Command Interview Questions and AnswersLong back I had once asked one of my friend why are you preparing Unix Command interview questions if you going for a Java Interview and he told me that this job doesn't only require knowledge of Java but also knowledge of Unix, Linux, SQL and other scripting language , which is quite true. After that I thought to collect various UNIX command interview questions asked to Java developers or trading system support interviews and this is the result of that compilation. This list of UNIX command interview questions are by means complete and would be great if you guys contribute some genuine and good Unix Command Interview questions and answers asked during interviews. I have divided the questions on three categories for sake of managing and keeping this list of Unix Interview questions up to date. Read more: http://javarevisited.blogspot.com/2011/05/unix-command-interview-questions.html#ixzz3W1UbYiXn

Overview: Microsoft Windows PowerShell command line shell and scripting language helps IT professionals achieve greater control and productivity. Using a new admin-focused scripting language, more than 130 standard command line tools, and consistent syntax and utilities, Windows PowerShell allows IT professionals to more easily control system administration and accelerate automation. ABOUT ECORPTRAININGS: Ecorp Trainings are one of the best institute providing quality level of training in E-learning process.This is instructor led online training. We also provide corporate training , if group of people interested in same technology. Contact us for detailed course content & register for a free demo. We also provide support in client interviews , resume preparation , ticket resolving. Contact us for custom designed training course by experts exclusively for yourself. We provide training for almost all IT technologies i.e ; JAVA , DOTNET , SAP ,ORACLE , PEOPLESOFT ,HYPERION etc, contact us if you have any particular need. ECORP TRAININGS. Gtalk ID : ecorptrainings Skype ID : ecorptrainings

PART I: EXPLORING SPLUNK Machine Data Basics Application Logs Web Access Logs Web Proxy Logs Call Detail Records Clickstream Data Message Queuing Packet Data Configuration Files Database Audit Logs and Tables File System Audit Logs Management and Logging APIs OS Metrics, Status, and Diagnostic Commands Other Machine Data Sources The Story of Splunk Splunk to the Rescue in the Datacenter Splunk to the Rescue in the Marketing Department Approaching Splunk Splunk: The Company and the Concept How Splunk Mastered Machine Data in the Datacenter Operational Intelligence Operational Intelligence at Work Getting Data In Machine Data Basics Types of Data Splunk Can Read Splunk Data Sources Downloading, Installing, and Starting Splunk Bringing Data in for Indexing Understanding How Splunk Indexes Data Searching with Splunk The Search Dashboard SPL™: Search Processing Language Pipes Implied AND top user fields – percent The search Command Tips for Using the search Command Subsearches SPL: Search Processing Language Sorting Results sort Filtering Results where dedup head Grouping Results transaction Reporting Results top stats chart timechart Filtering, Modifying, and Adding Fields fields replace eval rex lookup Enriching Your Data Using Splunk to Understand Data Identifying Fields: Looking at the Pieces of the Puzzle Exploring the Data to Understand its Scope Preparing for Reporting and Aggregation Visualizing Data Creating Visualizations Creating Dashboards Creating Alerts Creating Alerts through a Wizard Tuning Alerts Using Manager Customizing Actions for Alerting The Alerts Manager

sadguru technologies--040-40154733 Splunk to the Rescue in the Datacenter Splunk to the Rescue in the Marketing Department Approaching Splunk Splunk: The Company and the Concept How Splunk Mastered Machine Data in the Datacenter Operational Intelligence Operational Intelligence at Work A.Getting Data In Machine Data Basics Types of Data Splunk Can Read Splunk Data Sources Downloading, Installing, and Starting Splunk Bringing Data in for Indexing Understanding How Splunk Indexes Data B.Searching with Splunk The Search Dashboard SPL™: Search Processing Language Pipes Implied AND top user fields – percent The search Command Tips for Using the search Command Subsearches C.SPL: Search Processing Language Sorting Results

A.Getting Data In Machine Data Basics Types of Data Splunk Can Read Splunk Data Sources Downloading, Installing, and Starting Splunk Bringing Data in for Indexing Understanding How Splunk Indexes Data B.Searching with Splunk The Search Dashboard SPL™: Search Processing Language Pipes Implied AND top user fields – percent The search Command Tips for Using the search Command Subsearches C.SPL: Search Processing Language Sorting Results sort Filtering Results where dedup head Grouping Results transaction Reporting Results top stats chart timechart Filtering, Modifying, and Adding Fields fields replace

The Search Dashboard SPL™: Search Processing Language Pipes Implied AND top user fields – percent The search Command Tips for Using the search Command Subsearches C.SPL: Search Processing Language Sorting Results sort Filtering Results where dedup head Grouping Results transaction Reporting Results top stats chart timechart Filtering, Modifying, and Adding Fields fields replace eval

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HADOOP Training in Hyderabad @Sadguru Technologies Course Objective Summary During this course, you will learn: • Introduction to Big Data and Analytics • Introduction to Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • Sqoop concepts • Flume Concepts • Oozie workflow concepts • Impala Concepts • Hue Concepts • HBASE Concepts • ZooKeeper Concepts • Real Life Use Cases Reporting Tool • Tableau 1. Virtualbox/VM Ware • Basics • Installations • Backups • Snapshots 2. Linux • Basics • Installations • Commands 3. Hadoop • Why Hadoop? • Scaling • Distributed Framework • Hadoop v/s RDBMS • Brief history of hadoop 4. Setup hadoop • Pseudo mode • Cluster mode • Ipv6 • Ssh • Installation of java, hadoop • Configurations of hadoop • Hadoop Processes ( NN, SNN, JT, DN, TT) • Temporary directory • UI • Common errors when running hadoop cluster, solutions 5. HDFS- Hadoop distributed File System • HDFS Design and Architecture • HDFS Concepts • Interacting HDFS using command line • Interacting HDFS using Java APIs • Dataflow • Blocks • Replica 6. Hadoop Processes • Name node • Secondary name node • Job tracker • Task tracker • Data node 7. Map Reduce • Developing Map Reduce Application • Phases in Map Reduce Framework • Map Reduce Input and Output Formats • Advanced Concepts • Sample Applications • Combiner 8. Joining datasets in Mapreduce jobs • Map-side join • Reduce-Side join 9. Map reduce – customization • Custom Input format class • Hash Partitioner • Custom Partitioner • Sorting techniques • Custom Output format class

HADOOP Training in Hyderabad @Sadguru Technologies Course Objective Summary During this course, you will learn: • Introduction to Big Data and Analytics • Introduction to Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • Sqoop concepts • Flume Concepts • Oozie workflow concepts • Impala Concepts • Hue Concepts • HBASE Concepts • ZooKeeper Concepts • Real Life Use Cases Reporting Tool • Tableau 1. Virtualbox/VM Ware • Basics • Installations • Backups • Snapshots 2. Linux • Basics • Installations • Commands 3. Hadoop • Why Hadoop? • Scaling • Distributed Framework • Hadoop v/s RDBMS • Brief history of hadoop 4. Setup hadoop • Pseudo mode • Cluster mode • Ipv6 • Ssh • Installation of java, hadoop • Configurations of hadoop • Hadoop Processes ( NN, SNN, JT, DN, TT) • Temporary directory • UI • Common errors when running hadoop cluster, solutions 5. HDFS- Hadoop distributed File System • HDFS Design and Architecture • HDFS Concepts • Interacting HDFS using command line • Interacting HDFS using Java APIs • Dataflow • Blocks • Replica 6. Hadoop Processes • Name node • Secondary name node • Job tracker • Task tracker • Data node 7. Map Reduce • Developing Map Reduce Application • Phases in Map Reduce Framework • Map Reduce Input and Output Formats • Advanced Concepts • Sample Applications • Combiner 8. Joining datasets in Mapreduce jobs • Map-side join • Reduce-Side join 9. Map reduce – customization • Custom Input format class • Hash Partitioner • Custom Partitioner • Sorting techniques • Custom Output format class 10. Hadoop Programming Languages :- I.HIVE • Introduction • Installation and Configuration • Interacting HDFS using HIVE • Map Reduce Programs through HIVE • HIVE Commands • Loading, Filtering, Grouping…. • Data types, Operators….. • Joins, Groups…. • Sample programs in HIVE II. PIG • Basics • Installation and Configurations • Commands….

HADOOP Training in Hyderabad @Sadguru Technologies Course Objective Summary During this course, you will learn: • Introduction to Big Data and Analytics • Introduction to Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • Sqoop concepts • Flume Concepts • Oozie workflow concepts • Impala Concepts • Hue Concepts • HBASE Concepts • ZooKeeper Concepts • Real Life Use Cases Reporting Tool • Tableau 1. Virtualbox/VM Ware • Basics • Installations • Backups • Snapshots 2. Linux • Basics • Installations • Commands 3. Hadoop • Why Hadoop? • Scaling • Distributed Framework • Hadoop v/s RDBMS • Brief history of hadoop 4. Setup hadoop • Pseudo mode • Cluster mode • Ipv6 • Ssh • Installation of java, hadoop • Configurations of hadoop • Hadoop Processes ( NN, SNN, JT, DN, TT) • Temporary directory • UI • Common errors when running hadoop cluster, solutions 5. HDFS- Hadoop distributed File System • HDFS Design and Architecture • HDFS Concepts • Interacting HDFS using command line • Interacting HDFS using Java APIs • Dataflow • Blocks • Replica 6. Hadoop Processes • Name node • Secondary name node • Job tracker • Task tracker • Data node 7. Map Reduce • Developing Map Reduce Application • Phases in Map Reduce Framework • Map Reduce Input and Output Formats • Advanced Concepts • Sample Applications • Combiner 8. Joining datasets in Mapreduce jobs • Map-side join • Reduce-Side join 9. Map reduce – customization • Custom Input format class • Hash Partitioner • Custom Partitioner • Sorting techniques • Custom Output format class 10. Hadoop Programming Languages :- I.HIVE • Introduction • Installation and Configuration • Interacting HDFS using HIVE • Map Reduce Programs through HIVE • HIVE Commands • Loading, Filtering,

HADOOP Training in Hyderabad @Sadguru Technologies Course Objective Summary During this course, you will learn: • Introduction to Big Data and Analytics • Introduction to Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • Sqoop concepts • Flume Concepts • Oozie workflow concepts • Impala Concepts • Hue Concepts • HBASE Concepts • ZooKeeper Concepts • Real Life Use Cases Reporting Tool • Tableau 1. Virtualbox/VM Ware • Basics • Installations • Backups • Snapshots 2. Linux • Basics • Installations • Commands 3. Hadoop • Why Hadoop? • Scaling • Distributed Framework • Hadoop v/s RDBMS • Brief history of hadoop 4. Setup hadoop • Pseudo mode • Cluster mode • Ipv6 • Ssh • Installation of java, hadoop • Configurations of hadoop • Hadoop Processes ( NN, SNN, JT, DN, TT) • Temporary directory • UI • Common errors when running hadoop cluster, solutions 5. HDFS- Hadoop distributed File System • HDFS Design and Architecture • HDFS Concepts • Interacting HDFS using command line • Interacting HDFS using Java APIs • Dataflow • Blocks • Replica 6. Hadoop Processes • Name node • Secondary name node • Job tracker • Task tracker

HADOOP Training in Hyderabad @Sadguru Technologies Course Objective Summary During this course, you will learn: • Introduction to Big Data and Analytics • Introduction to Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • Sqoop concepts • Flume Concepts • Oozie workflow concepts • Impala Concepts • Hue Concepts • HBASE Concepts • ZooKeeper Concepts • Real Life Use Cases Reporting Tool • Tableau 1. Virtualbox/VM Ware • Basics • Installations • Backups • Snapshots 2. Linux • Basics • Installations • Commands 3. Hadoop • Why Hadoop? • Scaling • Distributed Framework • Hadoop v/s RDBMS • Brief history of hadoop 4. Setup hadoop • Pseudo mode • Cluster mode • Ipv6 • Ssh • Installation of java, hadoop • Configurations of hadoop • Hadoop Processes ( NN, SNN, JT, DN, TT) • Temporary directory • UI • Common errors when running hadoop cluster, solutions 5. HDFS- Hadoop distributed File System • HDFS Design and Architecture • HDFS Concepts • Interacting HDFS using command line • Interacting HDFS using Java APIs • Dataflow • Blocks

HADOOP Training in Hyderabad @Sadguru Technologies Course Objective Summary During this course, you will learn: • Introduction to Big Data and Analytics • Introduction to Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • Sqoop concepts • Flume Concepts • Oozie workflow concepts • Impala Concepts • Hue Concepts • HBASE Concepts • ZooKeeper Concepts • Real Life Use Cases Reporting Tool • Tableau 1. Virtualbox/VM Ware • Basics • Installations • Backups • Snapshots 2. Linux • Basics • Installations • Commands 3. Hadoop • Why Hadoop? • Scaling • Distributed Framework • Hadoop v/s RDBMS • Brief history of hadoop 4. Setup hadoop • Pseudo mode • Cluster mode • Ipv6 • Ssh • Installation of java, hadoop • Configurations of hadoop • Hadoop Processes ( NN, SNN, JT, DN, TT) • Temporary directory • UI • Common errors when running hadoop cluster, solutions 5. HDFS- Hadoop distributed File System • HDFS Design and Architecture • HDFS Concepts • Interacting HDFS using command line • Interacting HDFS using Java APIs • Dataflow • Blocks • Replica 6. Hadoop Processes • Name node • Secondary name node • Job tracker • Task tracker • Data node 7. Map Reduce • Developing Map Reduce Application • Phases in Map Reduce Framework • Map Reduce Input and Output Formats • Advanced Concepts • Sample Applications • Combiner 8. Joining datasets in Mapreduce jobs • Map-side join • Reduce-Side join 9. Map reduce – customization • Custom Input format class • Hash Partitioner • Custom Partitioner • Sorting techniques • Custom

HADOOP Training in Hyderabad @Sadguru Technologies Course Objective Summary During this course, you will learn: • Introduction to Big Data and Analytics • Introduction to Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • Sqoop concepts • Flume Concepts • Oozie workflow concepts • Impala Concepts • Hue Concepts • HBASE Concepts • ZooKeeper Concepts • Real Life Use Cases Reporting Tool • Tableau 1. Virtualbox/VM Ware • Basics • Installations • Backups • Snapshots 2. Linux • Basics • Installations • Commands 3. Hadoop • Why Hadoop? • Scaling • Distributed Framework • Hadoop v/s RDBMS • Brief history of hadoop 4. Setup hadoop • Pseudo mode • Cluster mode • Ipv6 • Ssh • Installation of java, hadoop • Configurations of hadoop • Hadoop Processes ( NN, SNN, JT, DN, TT) • Temporary directory • UI • Common errors when running hadoop cluster, solutions 5. HDFS- Hadoop distributed File System • HDFS Design and Architecture • HDFS Concepts • Interacting HDFS using command line • Interacting HDFS using Java APIs • Dataflow • Blocks • Replica 6. Hadoop Processes • Name node • Secondary name node • Job tracker • Task tracker • Data node 7. Map Reduce • Developing Map Reduce Application • Phases in Map Reduce Framework • Map Reduce Input and Output Formats • Advanced Concepts • Sample Applications • Combiner 8. Joining datasets in Mapreduce jobs • Map-side join • Reduce-Side join and...