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Features | Description |
Decentralised | Data is distributed across the cluster. There is no master node; every node can service any request. Each node contains different data |
Supports replication and multiple data centre replication | It has distrributed architecture. It can support multiple data centres for disaster recovery, redundancy |
Scalability | Easily scalable to various machines without any downtime or interruption to any applications |
Tunable consistency | It offers turable consistency for read and write operations. |
Mapreduce support | It has Hadoop integration with support for mapreduce, apache pig and apache hive |
Query language | It introduces cassandra query language |
2) Easy to use: Expose collection data types using relational concepts and standards for existing applications.
3) Codeless Implementation: Optimize performance and compatibility with any application without application changes.
4) Compatible: Certified Data Direct Quality guarantees Apache Cassandra compatibility through explicit testing
5) Fast: Easily load large volumes of data without application code or additional tools that slow performance
CREATE TABLE tbl_monthly ( station_id text, metrix text, date timestamp, location text, max int, mean int median int, min int, percentile1 int, percentile5 int, percentile95 int, total int, PRIMARY KEY((station_id), metric, date) ) CREATE TABLE tbl_station ( station_id text, location text, PRIMARY KEY (STATION_ID) ) |