Introduction to Spark 12
- What is Spark 30 minLecture1.1
- Why Spark 30 minLecture1.2
- Who Uses Spark 30 minLecture1.3
- Brief History of Spark 30 minLecture1.4
- Storage Layers for Spark 30 minLecture1.5
- Why Spark is 100 times faster than MapReduce 30 minLecture1.6
- Difference between Spark-1.x and Spark-2.x 30 minLecture1.7
- Unified Stack of Spark 30 minLecture1.8
- Spark Sql 30 minLecture1.9
- Spark Streaming 30 minLecture1.10
- Spark GraphX 30 minLecture1.11
- Spark MLLib 30 minLecture1.12
Spark Architecture explanation 4
- Master Slave architecture o o o 30 minLecture2.1
- Spark Driver 30 minLecture2.2
- Workers 30 minLecture2.3
- Executors 30 minLecture2.4
Installation of Spark in different modes 3
- Local mode 30 minLecture3.1
- Pseudo mode 30 minLecture3.2
- Cluster mode 30 minLecture3.3
Basics of Spark 11
- Creating the Spark ContextLecture4.1
- Creating the Spark ConfLecture4.2
- Creating the Spark SessionLecture4.3
- Configuring Spark Context with Spark ConfLecture4.4
- Caching OverviewLecture4.5
- Distributed PersistenceLecture4.6
- Combine scala and java seamlesslyLecture4.7
- Deploying Applications with spark-submitLecture4.8
- Verify spark jobs in Spark Web UILecture4.9
- SBTLecture4.10
- MAVENLecture4.11
Resilient Distributed Dataset (RDD) 4
- What is RDDLecture5.1
- Creating RDDsLecture5.2
- RDD OperationsLecture5.3
- Passing Functions to SparkLecture5.4
Working with Key/Value Pairs 8
- Creating Pair RDDs o Custom PartitionersLecture6.1
- Transformations on Pair RDDsLecture6.2
- – Aggregations o Grouping DataLecture6.3
- – JoinsLecture6.4
- – Sorting DataLecture6.5
- Data PartitioningLecture6.6
- – Determining an RDD’s PartitionerLecture6.7
- – Custom PartitionersLecture6.8
Loading and Saving Your Data 7
- File FormatsLecture7.1
- – Text, json, csv, tsv, Object filesLecture7.2
- – Hadoop Input and Output FormatsLecture7.3
- Loading Data using RDDLecture7.4
- Saving Data using RDDLecture7.5
- MapReduce and Pair RDD OperationsLecture7.6
- Scala and Hadoop IntegrationsLecture7.7
Broadcast and Accumulators 6
- Introduction to AccumulatorsLecture8.1
- Practical Examples on AccumulatorsLecture8.2
- Creating Custom AccumulatorsLecture8.3
- Introduction to Broadcast variables o Optimizing BroadcastsLecture8.4
- Practical Examples on Broadcast variablesLecture8.5
- Optimizing BroadcastsLecture8.6
Working with Spark in different programming languages 12
- Installing PythonLecture9.1
- How to use ‘pyspark’Lecture9.2
- Practical examples on spark in pythonLecture9.3
- Installing ScalaLecture9.4
- How to use ‘spark-shell’Lecture9.5
- Practical examples on spark in ScalaLecture9.6
- Installing JavaLecture9.7
- How to use ‘Java’Lecture9.8
- Practical examples on spark in JavaLecture9.9
- Installing RLecture9.10
- How to use ‘SparkR’Lecture9.11
- Practical examples on spark in RLecture9.12
Apache Spark SQL 9
- Spark SQL & Hive Architecture explanation Practical examples on Spark SQLLecture10.1
- Working with Spark SQL DataSetsLecture10.2
- Working with Spark SQL DataFramesLecture10.3
- Practice on Spark SQL ContextLecture10.4
- Integrating Spark SQL with o Hive o Phoenix o Cassandra o RDBMSLecture10.5
- Processing different files using Spark o Text o Json o Csv o Tsv o ParquetLecture10.6
- Spark SQL UDFsSpark SQL UDFsLecture10.7
- Spark SQL Performance Tuning OptionsLecture10.8
- JDBC/ODBC ServerLecture10.9
Apache Spark Streaming 10
- Spark Streaming Architecture explanationLecture11.1
- Creating the Streaming ContextLecture11.2
- Discretized Streams (DStreams)Lecture11.3
- Transformations on DstreamLecture11.4
- Output Operations on DStreamsLecture11.5
- Streaming UI explanationLecture11.6
- Spark Streaming Sources o Basic Sources o Advanced SourcesLecture11.7
- Integrating Spark Streaming with o Flume o Kafka o Twitter o HDFSLecture11.8
- Performance ConsiderationsLecture11.9
- Practical examples on Spark StreamingLecture11.10
Apache Spark MLib 4
- Machine Learning BasicsLecture12.1
- Machine Learning Algorithms o Classification o Clustering o Collaborative FilteringLecture12.2
- Performance ConsiderationsLecture12.3
- Practical examples on Spark MLibLecture12.4
Apache Spark Graphx 2
- Introduction to Spark GraphxLecture13.1
- Practical Examples on Spark GraphxLecture13.2
Apache Mesos 3
- Introduction to Apache MesosLecture14.1
- Apache Mesos Architecture explanationLecture14.2
- Practical Examples on Apache MesosLecture14.3
Apache Mahout 3
- Introduction to Apache MahoutLecture15.1
- Apache Mahout Architecture explanationLecture15.2
- Practical Examples on Apache MahoutLecture15.3
Apache Storm 3
- Introduction to Apache StormLecture16.1
- Apache Storm Architecture explanationLecture16.2
- Practical Examples on Apache StormLecture16.3
Apache Kafka 4
- Introduction to Apache KafkaLecture17.1
- Installing Apache KafkaLecture17.2
- Apache Kafka Architecture explanationLecture17.3
- Practical Examples on Apache KafkaLecture17.4
Apache FLUME 4
- Introduction to flumeLecture18.1
- Flume installationLecture18.2
- Flume Architecture o Agent o Sources o Channels o SinksLecture18.3
- Practical Examples on FlumeLecture18.4
Apache Phoenix 4
- Introduction to PhoenixLecture19.1
- Installing PhoenixLecture19.2
- Integrating with HbaseLecture19.3
- Practical Examples on PhoenixLecture19.4
Apache Cassandra 3
- Introduction to CassandraLecture20.1
- Installing CassandraLecture20.2
- Practical Examples on CassandraLecture20.3
Apache Drill 3
- Introduction to Drill Lecture21.1
- Installing DrillLecture21.2
- Practical Examples on DrillLecture21.3
Apache Zeppelin 4
- Introduction to ZeppelinLecture22.1
- Installing ZeppelinLecture22.2
- Practical Examples on ZeppelinLecture22.3
- Data Visualization using ZeppelinLecture22.4
Play Framework 4
- Introduction to Play FrameworkLecture23.1
- Installing Play FrameworkLecture23.2
- Practical Examples on Play FrameworkLecture23.3
- Spark Project using Play FrameworkLecture23.4
Introduction of Scala 6
- What is Scala?Lecture24.1
- Why Scala?Lecture24.2
- Advantages of Scala?Lecture24.3
- Using the Scala REPL(Read Evaluate print loop)Lecture24.4
- What is Type InferenceLecture24.5
- Interoperability between Scala and JavaLecture24.6
Scala using Command Line 4
- Installing Java & ScalaLecture25.1
- Interactive ScalaLecture25.2
- Writing Scala ScriptsLecture25.3
- Compiling Scala ProgramsLecture25.4
Basics of Scala 4
- Defining VariablesLecture26.1
- Defining FunctionsLecture26.2
- String InterpolationLecture26.3
- IDE for ScalaLecture26.4
Scala Type Less, Do More 11
- Semicolons Immutability Lecture27.1
- Variable DeclarationsLecture27.2
- Method DeclarationsLecture27.3
- Type InferenceLecture27.4
- ImmutabilityLecture27.5
- Reserved WordsLecture27.6
- OperatorsLecture27.7
- Precedence RulesLecture27.8
- LiteralsLecture27.9
- OptionsLecture27.10
- Arrays, Lists, Ranges, TuplesLecture27.11
Expressions and Conditionals 10
- If expressionsLecture28.1
- If-Else expressionsLecture28.2
- Match ExpressionsLecture28.3
- For LoopsLecture28.4
- While LoopsLecture28.5
- Do-While LoopsLecture28.6
- Conditional OperatorsLecture28.7
- EnumerationsLecture28.8
- Pattern MatchingLecture28.9
- Using try, catch, and finally ClausesLecture28.10
Functional Programming in Scala 10
- What is Functional Programming?Lecture29.1
- Functional Literals and ClosuresLecture29.2
- RecursionsLecture29.3
- Tail CallsLecture29.4
- CurryingLecture29.5
- Functional Data StructuresLecture29.6
- Sequences,Maps,SetsLecture29.7
- TraversingLecture29.8
- Traversal, Mapping, Filtering, Folding and ReducingLecture29.9
- Call by Name, Call by ValueLecture29.10
Object-Oriented Programming in Scala 10
- Class and Object BasicsLecture30.1
- Value ClassesLecture30.2
- Parent TypesLecture30.3
- Constructors in ScalaLecture30.4
- Fields in ClassesLecture30.5
- Nested TypesLecture30.6
- Traits as MixinsLecture30.7
- Stackable TraitsLecture30.8
- Creating TraitsLecture30.9
- Visibility RulesLecture30.10
Scala for Big Data 4
- Improving MapReduce with ScalaLecture31.1
- Moving Beyond MapReduceLecture31.2
- Categories for MathematicsLecture31.3
- A List of Scala-Based Data ToolsLecture31.4
Spark with Big Data Integrations: 6
- Spark and Hive integrationLecture32.1
- Saprk and Phoenix integrationLecture32.2
- Spark and Cassandra integrationLecture32.3
- Spark and Flume integrationLecture32.4
- Spark and Kafka integraionLecture32.5
- Spark and RDBMS integrationLecture32.6
Real Time Big Data Projects 4
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