Mock programs

FOR FREE DEMO contact us at: Phone/WhatsApp: +91-(850) 012-2107 HADOOP ONLINE TRAINING BY REALTIME CORPORATE PROFESSIONALS Hadoop Course Content (we can customize the course content as per your requirement) HADOOP Using Cloudera Development & Admin Course Introduction to BigData, Hadoop:- • Big Data Introduction • Hadoop Introduction • What is Hadoop? Why Hadoop? • Hadoop History? • Different types of Components in Hadoop? • HDFS, MapReduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on… • What is the scope of Hadoop? Deep Drive in HDFS (for Storing the Data):- • Introduction of HDFS • HDFS Design • HDFS role in Hadoop • Features of HDFS • Daemons of Hadoop and its functionality • Name Node • Secondary Name Node • Job Tracker • Data Node • Task Tracker • Anatomy of File Wright • Anatomy of File Read • Network Topology • Nodes • Racks • Data Center • Parallel Copying using DistCp • Basic Configuration for HDFS • Data Organization • Blocks and • Replication • Rack Awareness • Heartbeat Signal • How to Store the Data into HDFS • How to Read the Data from HDFS • Accessing HDFS (Introduction of Basic UNIX commands) • CLI commands MapReduce using Java (Processing the Data):- • Introduction of MapReduce. • MapReduce Architecture • Data flow in MapReduce • Splits • Mapper • Portioning • Sort and shuffle • Combiner • Reducer • Understand Difference Between Block and InputSplit • Role of RecordReader • Basic Configuration of MapReduce • MapReduce life cycle • Driver Code • Mapper • and Reducer • How MapReduce Works • Writing and Executing the Basic MapReduce Program using Java • Submission & Initialization of MapReduce Job. • File Input/output Formats in MapReduce Jobs • Text Input Format • Key Value Input Format • Sequence File Input Format • NLine Input Format • Joins • Map-side Joins • Reducer-side Joins • Word Count Example • Partition MapReduce Program • Side Data Distribution • Distributed Cache (with Program) • Counters (with Program) • Types of Counters • Task Counters • Job Counters • User Defined Counters • Propagation of Counters • Job Scheduling PIG:- • Introduction to Apache PIG • Introduction to PIG Data Flow Engine • MapReduce vs PIG in detail • When should PIG used? • Data Types in PIG • Basic PIG programming • Modes of Execution in PIG • Local Mode and • MapReduce Mode • Execution Mechanisms • Grunt Shell • Script • Embedded • Operators/Transformations in PIG • PIG UDF’s with Program • Word Count Example in PIG • The difference between the MapReduce and PIG SQOOP:- • Introduction to SQOOP • Use of SQOOP • Connect to mySql database • SQOOP commands • Import • Export • Eval • Codegen and etc… • Joins in SQOOP • Export to MySQL HIVE:- • Introduction to HIVE • HIVE Meta Store • HIVE Architecture • Tables in HIVE • Managed Tables • External Tables • Hive Data Types • Primitive Types • Complex Types • Partition • Joins in HIVE • HIVE UDF’s and UADF’s with Programs • Word Count Example HBASE:- • Introduction to HBASE • Basic Configurations of HBASE • Fundamentals of HBase • What is NoSQL? • HBase DataModel • Table and Row • Column Family and Column Qualifier • Cell and its Versioning • Categories of NoSQL Data Bases • Key-Value Database • Document Database • Column Family Database • SQL vs NOSQL • How HBASE is differ from RDBMS • HDFS vs HBase • Client side buffering or bulk uploads • HBase Designing Tables • HBase Operations • Get • Scan • Put • Delete MongoDB:-- • What is MongoDB? • Where to Use? • Configuration On Windows • Inserting the data into MongoDB? • Reading the MongoDB data. Cluster Setup:-- • Downloading and installing the Ubuntu12.x • Installing Java • Installing Hadoop • Creating Cluster • Increasing Decreasing the Cluster size • Monitoring the Cluster Health • Starting and Stopping the Nodes OOZIE • Introduction to OOZIE • Use of OOZIE • Where to use? Hadoop Ecosystem Overview Oozie HBase Pig Sqoop Casandra Chukwa Mahout Zoo Keeper Flume • Case Studies Discussions • Certification Guidance • Real Time Certification and • interview Questions and Answers • Resume Preparation • Providing all Materials nd Links • Real time Project Explanation and Practice Phone/WhatsApp: +91-(850) 012-2107

BIGDATA –HADOOP REALTIME TRAINING,JOB SUPPORT,INTERVIEW SUPPORT BY HANDS-ON EXPERTS Phone/WhatsApp: +91-(850) 012-2107 Course Content HADOOP Using Cloudera Development & Admin Course Introduction to BigData, Hadoop:- • Big Data Introduction • Hadoop Introduction • What is Hadoop? Why Hadoop? • Hadoop History? • Different types of Components in Hadoop? • HDFS, MapReduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on… • What is the scope of Hadoop? Deep Drive in HDFS (for Storing the Data):- • Introduction of HDFS • HDFS Design • HDFS role in Hadoop • Features of HDFS • Daemons of Hadoop and its functionality • Name Node • Secondary Name Node • Job Tracker • Data Node • Task Tracker • Anatomy of File Wright • Anatomy of File Read • Network Topology • Nodes • Racks • Data Center • Parallel Copying using DistCp • Basic Configuration for HDFS • Data Organization • Blocks and • Replication • Rack Awareness • Heartbeat Signal • How to Store the Data into HDFS • How to Read the Data from HDFS • Accessing HDFS (Introduction of Basic UNIX commands) • CLI commands MapReduce using Java (Processing the Data):- • Introduction of MapReduce. • MapReduce Architecture • Data flow in MapReduce • Splits • Mapper • Portioning • Sort and shuffle • Combiner • Reducer • Understand Difference Between Block and InputSplit • Role of RecordReader • Basic Configuration of MapReduce • MapReduce life cycle • Driver Code • Mapper • and Reducer • How MapReduce Works • Writing and Executing the Basic MapReduce Program using Java • Submission & Initialization of MapReduce Job. • File Input/output Formats in MapReduce Jobs • Text Input Format • Key Value Input Format • Sequence File Input Format • NLine Input Format • Joins • Map-side Joins • Reducer-side Joins • Word Count Example • Partition MapReduce Program • Side Data Distribution • Distributed Cache (with Program) • Counters (with Program) • Types of Counters • Task Counters • Job Counters • User Defined Counters • Propagation of Counters • Job Scheduling PIG:- • Introduction to Apache PIG • Introduction to PIG Data Flow Engine • MapReduce vs PIG in detail • When should PIG used? • Data Types in PIG • Basic PIG programming • Modes of Execution in PIG • Local Mode and • MapReduce Mode • Execution Mechanisms • Grunt Shell • Script • Embedded • Operators/Transformations in PIG • PIG UDF’s with Program • Word Count Example in PIG • The difference between the MapReduce and PIG SQOOP:- • Introduction to SQOOP • Use of SQOOP • Connect to mySql database • SQOOP commands • Import • Export • Eval • Codegen and etc… • Joins in SQOOP • Export to MySQL HIVE:- • Introduction to HIVE • HIVE Meta Store • HIVE Architecture • Tables in HIVE • Managed Tables • External Tables • Hive Data Types • Primitive Types • Complex Types • Partition • Joins in HIVE • HIVE UDF’s and UADF’s with Programs • Word Count Example HBASE:- • Introduction to HBASE • Basic Configurations of HBASE • Fundamentals of HBase • What is NoSQL? • HBase DataModel • Table and Row • Column Family and Column Qualifier • Cell and its Versioning • Categories of NoSQL Data Bases • Key-Value Database • Document Database • Column Family Database • SQL vs NOSQL • How HBASE is differ from RDBMS • HDFS vs HBase • Client side buffering or bulk uploads • HBase Designing Tables • HBase Operations • Get • Scan • Put • Delete MongoDB:-- • What is MongoDB? • Where to Use? • Configuration On Windows • Inserting the data into MongoDB? • Reading the MongoDB data. Cluster Setup:-- • Downloading and installing the Ubuntu12.x • Installing Java • Installing Hadoop • Creating Cluster • Increasing Decreasing the Cluster size • Monitoring the Cluster Health • Starting and Stopping the Nodes OOZIE • Introduction to OOZIE • Use of OOZIE • Where to use? Hadoop Ecosystem Overview Oozie HBase Pig Sqoop Casandra Chukwa Mahout Zoo Keeper Flume • Case Studies Discussions • Certification Guidance • Real Time Certification and • interview Questions and Answers • Resume Preparation • Providing all Materials nd Links • Real time Project Explanation and Practice

BEST HADOOP LIVE TRAINING BY REALTIME CORPORATE PROFESSIONALS Hadoop Course Agenda (we can customize the course content as per your requirement) HADOOP Using Cloudera Development & Admin Course Introduction to BigData, Hadoop:- • Big Data Introduction • Hadoop Introduction • What is Hadoop? Why Hadoop? • Hadoop History? • Different types of Components in Hadoop? • HDFS, MapReduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on… • What is the scope of Hadoop? Deep Drive in HDFS (for Storing the Data):- • Introduction of HDFS • HDFS Design • HDFS role in Hadoop • Features of HDFS • Daemons of Hadoop and its functionality • Name Node • Secondary Name Node • Job Tracker • Data Node • Task Tracker • Anatomy of File Wright • Anatomy of File Read • Network Topology • Nodes • Racks • Data Center • Parallel Copying using DistCp • Basic Configuration for HDFS • Data Organization • Blocks and • Replication • Rack Awareness • Heartbeat Signal • How to Store the Data into HDFS • How to Read the Data from HDFS • Accessing HDFS (Introduction of Basic UNIX commands) • CLI commands MapReduce using Java (Processing the Data):- • Introduction of MapReduce. • MapReduce Architecture • Data flow in MapReduce • Splits • Mapper • Portioning • Sort and shuffle • Combiner • Reducer • Understand Difference Between Block and InputSplit • Role of RecordReader • Basic Configuration of MapReduce • MapReduce life cycle • Driver Code • Mapper • and Reducer • How MapReduce Works • Writing and Executing the Basic MapReduce Program using Java • Submission & Initialization of MapReduce Job. • File Input/output Formats in MapReduce Jobs • Text Input Format • Key Value Input Format • Sequence File Input Format • NLine Input Format • Joins • Map-side Joins • Reducer-side Joins • Word Count Example • Partition MapReduce Program • Side Data Distribution • Distributed Cache (with Program) • Counters (with Program) • Types of Counters • Task Counters • Job Counters • User Defined Counters • Propagation of Counters • Job Scheduling PIG:- • Introduction to Apache PIG • Introduction to PIG Data Flow Engine • MapReduce vs PIG in detail • When should PIG used? • Data Types in PIG • Basic PIG programming • Modes of Execution in PIG • Local Mode and • MapReduce Mode • Execution Mechanisms • Grunt Shell • Script • Embedded • Operators/Transformations in PIG • PIG UDF’s with Program • Word Count Example in PIG • The difference between the MapReduce and PIG SQOOP:- • Introduction to SQOOP • Use of SQOOP • Connect to mySql database • SQOOP commands • Import • Export • Eval • Codegen and etc… • Joins in SQOOP • Export to MySQL HIVE:- • Introduction to HIVE • HIVE Meta Store • HIVE Architecture • Tables in HIVE • Managed Tables • External Tables • Hive Data Types • Primitive Types • Complex Types • Partition • Joins in HIVE • HIVE UDF’s and UADF’s with Programs • Word Count Example HBASE:- • Introduction to HBASE • Basic Configurations of HBASE • Fundamentals of HBase • What is NoSQL? • HBase DataModel • Table and Row • Column Family and Column Qualifier • Cell and its Versioning • Categories of NoSQL Data Bases • Key-Value Database • Document Database • Column Family Database • SQL vs NOSQL • How HBASE is differ from RDBMS • HDFS vs HBase • Client side buffering or bulk uploads • HBase Designing Tables • HBase Operations • Get • Scan • Put • Delete MongoDB:-- • What is MongoDB? • Where to Use? • Configuration On Windows • Inserting the data into MongoDB? • Reading the MongoDB data. Cluster Setup:-- • Downloading and installing the Ubuntu12.x • Installing Java • Installing Hadoop • Creating Cluster • Increasing Decreasing the Cluster size • Monitoring the Cluster Health • Starting and Stopping the Nodes OOZIE • Introduction to OOZIE • Use of OOZIE • Where to use? Hadoop Ecosystem Overview Oozie HBase Pig Sqoop Casandra Chukwa Mahout Zoo Keeper Flume • Case Studies Discussions • Certification Guidance • Real Time Certification and • interview Questions and Answers • Resume Preparation • Providing all Materials nd Links • Real time Project Explanation and Practice

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BASE SAS MODULES Day 1: Introduction to the SAS System Components of Base SAS Software Output Produced by the SAS System Ways to Run SAS Programs Running Programs in the SAS Windowing Environment Introduction to DATA Step Processing The SAS Data Set introduction How the DATA Step Works: A Basic Introduction Supplying Information to Create a SAS Data Set Introduction to Raw Data Examine the Structure of the Raw Data: Factors to Consider Reading Unaligned Data Reading Data That Is Aligned in Columns Reading Data That Requires Special Instructions Reading Unaligned Data with More Flexibility Mixing Styles of Input Day 2: Introduction to Beyond the Basics with Raw Data Using INFILE statement and various options. Testing a Condition before Creating an Observation Creating Multiple Observations from a Single Record Reading Multiple Records to Create a Single Observation Problem Solving: When an Input Record Unexpectedly Does Not have enough values Day 3: Introduction to Starting with SAS Data Sets Understanding the Basics Input SAS Data Set for Examples Reading Selected Observations Reading Selected Variables Creating More Than One Data Set in a Single DATA Step Using the DROP=, KEEP= and WHERE= Data Set Options for Efficiency Introduction to DATA Step Processing Input SAS Data Set for Examples Adding Information to a SAS Data Set Defining Enough Storage Space for Variables Conditionally Deleting an Observation Day 4: Introduction to Working with Numeric Variables About Numeric Variables in SAS Input SAS Data Set for Examples Calculating with Numeric Variables Comparing Numeric Variables Storing Numeric Variables Efficiently Numeric Functions. Day 5: Introduction to Working with Character Variables Input SAS Data Set for Examples Identifying Character Variables and Expressing Character Values Handling Missing Values Creating New Character Values Saving Storage Space by Treating Numbers as Characters Character Functions Day 6: Introduction to Acting on Selected Observations Input SAS Data Set for Examples Selecting Observations Constructing Conditions Comparing Characters Introduction to Creating Subsets of Observations Input SAS Data Set for Examples Selecting Observations for a New SAS Data Set Conditionally Writing Observations to One or More SAS Data Sets Day 7: Introduction to Working with Grouped or Sorted Observations Input SAS Data Set for Examples Working with Grouped Data Working with Sorted Data Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Day 8: Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Introduction to Working with Dates Understanding How SAS Handles Dates Input File and SAS Data Set for Examples Entering Dates Displaying Dates Using Dates in Calculations Using SAS Date Functions Comparing Durations and SAS Date Values Day 9: Introduction to Combining SAS Data Sets Definition of Concatenating Definition of Interleaving Definition of Merging Definition of Updating Definition of Modifying 237 Comparing Modifying, Merging, and Updating Data Sets Day 10: Introduction to Concatenating SAS Data Sets Concatenating Data Sets with the SET Statement Concatenating Data Sets Using the APPEND Procedure Choosing between the SET Statement and the APPEND Procedure. Introduction to Interleaving SAS Data Sets Understanding BY-Group Processing Concepts Interleaving Data Sets Day 11: Introduction to Merging SAS Data Sets Understanding the MERGE Statement One-to-One Merging Match-Merging Choosing between One-to-One Merging and Match-Merging Introduction to Updating SAS Data Sets Understanding the UPDATE Statement Understanding How to Select BY Variables Updating a Data Set Updating with Incremental Values Understanding the Differences between Updating and Merging Handling Missing Values Day 12: Input SAS Data Set for Examples Modifying a SAS Data Set: The Simplest Case Modifying a Master Data Set with Observations from a Transaction Data Set Understanding How Duplicate BY Variables Affect File Update Handling Missing Values Introduction to Conditional Processing from Multiple SAS Data Sets Input SAS Data Sets for Examples Determining Which Data Set Contributed the Observation Combining Selected Observations from Multiple Data Sets Performing a Calculation Based on the Last Observation Day 13: Introduction to Analysing Your SAS Session with the SAS Log Understanding the SAS Log Locating the SAS Log Understanding the Log Structure Writing to the SAS Log Suppressing Information to the SAS Log Changing the Log’s Appearance Introduction to Directing SAS Output and the SAS Log Input File and SAS Data Set for Examples Routing the Output and the SAS Log with PROC PRINTTO Storing the Output and the SAS Log in the SAS Windowing Environment Redefining the Default Destination in a Batch or Non interactive Environment Introduction to Diagnosing and Avoiding Errors Understanding How the SAS Supervisor Checks a Job Understanding How SAS Processes Errors Distinguishing Types of Errors Diagnosing Errors Using a Quality Control Checklist Day 14: Introduction to Creating Detail and Summary Reports with the REPORT Procedure Understanding How to Construct a Report Input File and SAS Data Set for Examples Creating Simple Reports Creating More Sophisticated Reports Day 15: Introduction to Proc means Deriving descriptive statistics Introduction to Proc univariate and various options Day 16: Introduction to Proc freq Calculating counts using Freq Outputting the counts into a dataset Proc Transpose introduction Using VAR, ID and BY statement efficiently in transpose Reshaping the data with required variables Day 17: Introduction to Producing Charts to Summarize Variables Understanding the Charting Tools Input File and SAS Data Set for Examples Charting Frequencies with the CHART Procedure Customizing Frequency Charts Creating High-Resolution Histograms Day 18: Introduction to Writing Lines to the SAS Log or to an Output File Understanding the PUT Statement Writing Output without Creating a Data Set Writing Simple Text Introduction to the Basics of Understanding and Customizing SAS Output Understanding Output Input SAS Data Set for Examples Locating Procedure Output Making Output Informative Controlling Output Appearance Controlling the Appearance of Pages Representing Missing Values Day 19: Introduction to Customizing SAS Output by Using the Output Delivery System Input Data Set for Examples Understanding ODS Output Formats and Destinations Selecting an Output Format Creating Formatted Output Day 20: Proc Format introduction Creating format catalogue Converting catalogue to dataset Storing formats permanently and finding out formats in a library Accessing a Permanent SAS Data Set with User-Defined Formats ADVANCED SAS MODULES Day 21: Getting Started with the Macro Facility Replacing Text Strings Using Macro Variables Generating SAS Code Using Macros More Advanced Macro Techniques Other Features of the Macro Language Introduction to SAS Programs and Macro Processing How SAS Processes Statements without Macro Activity How SAS Processes Statements with Macro Activity Introduction to Macro Variables Macro Variables Defined by SAS Macro Variables Defined by Users Using Macro Variables Displaying Macro Variable Values Referencing Macro Variables Indirectly Manipulating Macro Variable Values with Macro Functions Introduction to Macro Processing Defining and Calling Macros How the Macro Processor Compiles a Macro Definition How the Macro Processor Executes a Compiled Macro Summary of Macro Processing Day 22: Introduction to the Scopes of Macro Variables Global Macro Variables Local Macro Variables Writing the Contents of Symbol Tables to the SAS Log How Macro Variables Are Assigned and Resolved Introduction to Macro Expressions Defining Arithmetic and Logical Expressions How the Macro Processor Evaluates Arithmetic Expressions Day 23: Introduction to Macro Quoting Deciding When to Use a Macro Quoting Function and Which Function to Use Using Various Macro Functions %STR and %NRSTR Functions etc Using the %BQUOTE and %NRBQUOTE Functions Referring to Already Quoted Variables Deciding How Much Text to Mask with a Macro Quoting Function Using %SUPERQ Summary of Macro Quoting Functions and 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