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Data orientation is the representation of tabular data in a linear memory model such as in-disk or in-memory. The two most common representations are column-oriented (columnar format) and row-oriented (row format). [1] [2] The choice of data orientation is a trade-off and an architectural decision in databases, query engines, and numerical ...
Does not free the space occupied by the data in the table (in the TABLESPACE) Does not reset the SEQUENCE value assigned to the table; DELETE works much slower than TRUNCATE; You can undo the operation of removing records by using the ROLLBACK command; DELETE requires a shared table lock; Triggers fire; DELETE can be used in the case of ...
SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example, which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
Apache ORC (Optimized Row Columnar) is a free and open-source column-oriented data storage format. [3] It is similar to the other columnar-storage file formats available in the Hadoop ecosystem such as RCFile and Parquet. It is used by most of the data processing frameworks Apache Spark, Apache Hive, Apache Flink, and Apache Hadoop.
Apache Parquet is a free and open-source column-oriented data storage format in the Apache Hadoop ecosystem. It is similar to RCFile and ORC, the other columnar-storage file formats in Hadoop, and is compatible with most of the data processing frameworks around Hadoop.
In SQL, the data manipulation language comprises the SQL-data change statements, [3] which modify stored data but not the schema or database objects. Manipulation of persistent database objects, e.g., tables or stored procedures, via the SQL schema statements, [3] rather than the data stored within them, is considered to be part of a separate data definition language (DDL).
In order not to fill the data store with useless information, there is a policy to remove tombstones completely. For this, the system checks the age of the tombstone and removes it after a prescribed time has elapsed. In Apache Cassandra, this elapsed time is set with the GCGraceSeconds parameter [1] and the process is named Compaction. [2]