Learn by Example : HBase - The Hadoop Database

Insert data into an HBase base table using the space shell and put command, adding one cell per row and column, such as attributes:user with value Chaz.

Update a row in HBase with the put command to create or modify a row and its open column, preserving history with timestamps; get returns the latest version.

Use the get command to retrieve all columns for a row id in HBase by default. Fetch specific columns or cells, and view the row–column family–cell hierarchy with timestamps.

Delete operations remove data from a base table using the delete command in the base shell, illustrating single-cell deletes and removal of a row when all columns are cleared.

Delete a table in the space shell by disabling it to flush changes to disk, then run the drop command and verify removal with the list command.

Insert or update a single row in an HBase table using the Java Put object, by specifying row id, column family, column, and value as byte arrays.

Insert multiple rows in HBase by batching puts: create a list of put objects for two row IDs, add columns, and execute a bulk put on the edge table.

Demonstrates retrieving a single row from HBase using the Java get object: specify row id, column family, and column, connect to the table, and read values from the result map.

Fetch data for multiple row IDs with a list of get objects, specifying column families and column names as byte arrays, then call the table's get method.

Delete a value from a single row in hbase by using the delete class with a row id and column family and column, then call edge table's delete method.

Perform scan operations to retrieve a range of rows by row IDs using a scan object and result scanner; customize to return all data or specific columns.

Explore how the edge-based HBase architecture, inspired by Google Bigtable, stores data as data points in a column-oriented nested map with region servers, memstore, write-ahead logs, and HFile on HDFS.

Explore how to retrieve data by applying a filter in HBase, using scans with start and stop rows and a row filter with equals operators and binary comparator.

Use a single column value filter on a scan to select row IDs whose user column equals a value, returning all columns for matching rows.

Apply multiple conditions by using a filter list to combine two single column value filters, selecting row IDs where for_user equals Daniel and type equals friend request.

Learn to increment metrics atomically in HBase using counters, replacing read-modify-write with a single increment operation that handles views, opens, and clicks for a row.