By Nishant Garg
A functional consultant to knowing the seamless strength of storing and coping with high-volume, high-velocity information fast and painlessly with HBase
About This Book
- Learn how one can use HBase successfully to shop and deal with never-ending quantities of data
- Discover the intricacies of HBase internals, schema designing, and contours like facts scanning and filtration
- Optimize your huge information administration and BI utilizing functional implementations
Who This ebook Is For
This booklet is meant for builders and large information engineers who need to know all approximately HBase at a hands-on point. For in-depth realizing, it'd be precious to have a little bit familiarity with HDFS and MapReduce programming ideas with out earlier adventure with HBase or comparable applied sciences. This booklet can also be for large facts lovers and database builders who've labored with different NoSQL databases and now are looking to discover HBase as one other futuristic, scalable database resolution within the significant info space.
What you'll Learn
- Realize the necessity for HBase
- Download and manage HBase cluster
- Grasp info modeling recommendations in HBase and the way to accomplish CRUD operations on data
- Perform powerful information scanning and knowledge filtration in HBase
- Understand info garage and replication in HBase
- Explore HBase counters, coprocessors, and MapReduce integration
- Get conversant in various consumers of HBase akin to relaxation and Kundera ORM
- Learn approximately cluster administration and function tuning in HBase
With an example-oriented strategy, this ebook starts off via giving you a step by step studying procedure to without problems organize HBase clusters and layout schemas. progressively, you may be taken via complicated information modeling techniques and the intricacies of the HBase structure. additionally, additionally, you will get conversant in the HBase patron API and HBase shell. basically, this ebook goals to supply you with an excellent grounding within the NoSQL columnar database house and likewise is helping you are taking good thing about the genuine energy of HBase utilizing info scans, filters, and the MapReduce framework. most significantly, the booklet additionally offers you sensible use circumstances masking a variety of HBase consumers, HBase cluster management, and function tuning.
Read Online or Download HBase Essentials PDF
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Additional info for HBase Essentials
SetTimeStamp(long timestamp) Gets versions of columns with the specified timestamp. setMaxVersions(int maxVersions) Gets up to the specified number of versions of each column. The default value of the maximum version returned is 1 which is the latest cell value. setFilter(Filter filter) Applies the specified server-side filter when performing the query. setStartRow(byte startRow) Sets the start row of the scan. setStopRow(byte stopRow) Sets the stop row. Gets all columns from the specified family.
Hadoop. client package. This class provides the user with all the functionality needed to store and retrieve data: HTableInterface usersTable = new HTable("Costumers"); From the preceding code, we can verify that the usage of the HConnection and HConnectionManager classes is not mandatory as the HTable constructor reads the default configuration to create a connection. getTable("Costumers"); [ 27 ] Defining the Schema The HTable class is not thread-safe as concurrent modifications are not safe.
META table. 0 onwards, the -ROOT- table is removed. META table is renamed as hbase:meta. META is stored in ZooKeeper. The following is the structure of the hbase:meta table. Key—the region key of the format ([table],[region start key],[region id]). A region with an empty start key is the first region in a table. The values are as follows: • info:regioninfo (serialized the HRegionInfo instance for this region) • info:server (server:port of the RegionServer containing this region) • info:serverstartcode (start time of the RegionServer process that contains this region) When the table is split, two new columns will be created as info:splitA and info:splitB.