HBase

HBase course is offered by Anika Technologies. Anika Technologies offers comprehensive training programs that cover a wide range of topics, including emerging technologies, software development methodologies, data analytics, cybersecurity, cloud computing, and more.

These training programs are designed to cater to the specific needs and objectives of businesses, ensuring that participants gain practical insights and hands-on experience.

Content:

• Introduction
• Dynamo and Bigtable
• Key/Value Stores
• Schemaless
• Common Advantages
• What am I giving up?
• BigTable and HBase(C + P)
• Data Mode
• Table, Column Families,Rows and Columns
• HBase Storage Architecture
• Physical Architecture
• Role of Zookeeper
• HMaster and HRegionServer
• Root Table and Meta Table
• MemStore
• WAL
• HFile
• Read and Write Path
• How Data is Store in Hfile
• Key Format
• HFile Format
• Log Structures Merge Trees
• Limitations of Binary Trees
• Limitations of B+ Trees
• LogStructured Merge tree as the back bone of storage
• Compaction
• Future Directions
• Exploring OFF-Heap Storage
• MMap for bloom filters and Block indexes
• HBase Operations
• Access Patterns
• Gets
• Caching
• Put
• Batching
• Scanning
• Filters
• Desiging HBase Tables and Schemas
• Key Design
• Concepts
• Tall-Narrow Versus Flat-Wide Tables
• Partial Key Scans
• Pagination
• Time Series Data
• Time-Ordered Relations
• Advanced Schemas
• Secondary Indexes
• Advanced Map Reduce
• Controlling MapReduce Execution with InputFormat
• Implementing InputFormat for Compute-Intensive Applications
• Implementing InputFormat to Control the Number of Maps
• Implementing InputFormat for Multiple HBase Tables
• Reading Data Your Way with Custom RecordReaders
• Implementing a Queue-Based RecordReader
• Implementing RecordReader for XML Data
• Organizing Output Data with Custom Output Formats
• Implementing OutputFormat for Splitting MapReduce
• Job’s Output into Multiple Directories
• Writing Data Your Way with Custom RecordWriters
• Implementing a RecordWriter to Produce Output tar Files
• Optimizing Your MapReduce Execution with a Combiner
• Controlling Reducer Execution with Partitioners
• Implementing a Custom Partitioner for One-to-Many Joins
• Using Non-Java Code with Hadoop
• Pipes
• Hadoop Streaming
• Using JNI
• Real-Time Case-Study
• Using HBase for Implementing Real-Time Applications
• Using HBase as a Picture Management System
• Understanding HBase Limitations and Opportunities
• Understanding indexing with HBase
• Optimizing HBase for indexing
• Where is the data stored?
• Combining HBase and HDFS
• Using HBase as a Lucene Back End
• Lucene Refresher
• Limitaions of Lucene
• Designing Lucene to Use Sharded Index with HBase
• Where is the data stored?
• Combining Lucene, HBase and HDFS
• Hey, did we just design Solr?