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HBase Vs RDBMS
H Base Vs RDBMS:
H BASE and other column-oriented DATABASE are often compared to more traditional and popular relational database or RDBMS.
| H Base | RDBMS |
| 1. Column-oriented | 1. Row-oriented(mostly) |
| 2. Flexible schema, add columns on the Fly | 2. Fixed schema |
| 3. Good with sparse tables. | 3. Not optimized for sparse tables. |
| 4. No query language | 4. SQL |
| 5. Wide tables | 5. Narrow tables |
| 6. Joins using MR – not optimized | 6. optimized for Joins(small, fast ones) |
| 7. Tight – Integration with MR | 7. Not really |
| 8. De-normalize your data. | 8. Normalize as you can |
| 9. Horizontal scalability-just add hard war. | 9. Hard to share and scale. |
| 10. Consistent | 10. Consistent |
| 11. No transactions. | 11. transactional |
| 12. Good for semi-structured data as well as structured data. | 12. Good for structured data. |
Basis CRUD Operations in H Base:
- If you want any CRUD Operations in H Base, H Base should be up and running otherwise the operations will not be successful.
- Running the child instance, but not running the master instance is not same as the running master instance as creating the child instance.
- The initial sets of basic operations are often referred to as CRUD which stands for Create, Read, Update and Delete.
- These are provided by the HTable class.
- Whenever we are creating a table name in H Base, we must follow the below steps:
- For creating a table, the syntax is
H Base (main):002:0>create ‘table name’, ’column family Name’
Ex:-H Base (main):002:0>create ‘Hadoop Table’, ’column1’, ’column2’
We can’t delete column family names.
To insert data, the commands are
hbase (main):002:0> put ‘Hadoop Table’, ’row1’, ’ Hadoop: HDRS’, ‘For storage’ h base (main):002:0> put ‘Hadoop Table’, ’row2’, ’ Hadoop: Map Reduce’, For Processing’ h base (main):002:0> put ‘Hadoop Table’, ’row3’, ’ Hadoop: Hive’,’ For Warehouse’ h base (main):002:0> put ‘Hadoop Table’, ’row4’, ’ Hadoop: H Base’,’ For Reads and write’
To see the data, a command is
hbase (main):002:0> scan ‘Hadoop Table’, (like select stmt)
we can see the records of the table.
- To get the particular row, cmd is
Hbase(main):002:0> get ‘Hadoop Table’, ‘row2’
- To insert the multiple columns at a time, cmd is
h base (main):002:0> put ‘Hadoop Table’, ‘row4’ Hadoop: pig, hue, zookeeper’ ‘different components of hadoop’
- To delete the row, cmd is
hbase(main):002:0> Delete ‘Hadoop Table’, ‘row4’‘Hadoop:Hive’
We can delete the complete row, but cannot delete the individual value of the row.
- To insert the new row with same row key i.e with no overriding concept and it will append, Example as below
Hbase(main):002:0> put ‘Hadoop Table’, ‘row2’‘Hadoop:New map reduce’ ‘New one’
- Based on the version ID, we will insert the values in H Base.
- To check the count of records, cmd is
hbase(main):002:0> count ‘Hadoop Table’
- To check whether the table exists or not
H base(main):002:0> Exist ‘Hadoop Table’
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List of Other Big Data Courses:
| Hadoop Administration | MapReduce |
| Big Data On AWS | Informatica Big Data Integration |
| Bigdata Greenplum DBA | Informatica Big Data Edition |
| Hadoop Hive | Impala |
| Hadoop Testing | Apache Mahout |
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