While Distributing the load, problem is Sequential keys such as timestamps will go to the same region to solve this issue Prefix key with a hash or other well distributed value for better throughput of writes
Question :
While schema design which of the following is valid point to keeping StoreFile indices small..
While Schema Design Large StoreFile indices - Every cell always includes row, column name and timestamp - Indices are kept in HBase StoreFiles to facilitate random access - Large cell value coordinates increase the size of indices - May occupy large chunks of RAM - Compression also increases the size of indices Increase the block size - Store file index will happened at a larger interval Keep names small - Keep ColumnFamily names as small as possible - Avoid long verbose attribute names - Keep RowKey length as short as is reasonable
Question :
For storing the data in HBase Anything that can be converted to an array of bytes can be stored 1. True 2. False
Bytes-in/bytes-out interface Anything that can be converted to an array of bytes can be stored - Input can be strings, numbers, complex objects, images, etc.
Question : In which of the following scenerio we should use HBase 1. If it require random read, write or both 2. If it requires to do many thousands of operations per second on multiple TB of data 3. If access pattern is well known and simple 4. All of the above
1. You only append to your dataset, and tend to read the whole thing 2. For ad-hoc analytics 3. If data volume is quite small 4. All of the above 5. None of the above
operation on HBase table 1. Syntex for count is count 'tablename' [, interval] 2. Counting the rows of a large table can be slow 3. The progress will be reported every interval 4. None of the 1,2 and 3 5. Only 1 and 2