New Features in Version 4.2
The following features were introduced in Vector 4.2:
• Query level auditing (C2 security)
• Data at rest encryption allows specific table columns to be encrypted.
• Statements MODIFY…TO COMBINE and MODIFY…TO RECONSTRUCT replace the COMBINE and REWRITE forms of the CALL X100 statement, which are deprecated.
• CALL X100 is now a privileged operation that requires the user to have DB_ADMIN database privileges. This feature has upgrade considerations.
• SET INSERTMODE statement lets you control whether inserts go through the PDT (memory) or directly to disk.
• The CREATE STATISTICS and DROP STATISTICS statements create and delete statistics and histograms on specified tables and columns. They allow applications to manipulate statistics from within a transaction. Also, new options on COPY FROM and vwload that create statistics on the table just loaded.
• INTERSECT and EXCEPT set operators for use in the same context as UNION in selects. INTERSECT returns only rows that appear in both result tables. EXCEPT returns the rows of the first result table that do not appear in the second result table.
• CREATE TABLE IF NOT EXISTS statement creates the table if it does not exist and returns without error if the table exists.
• The following additions to aggregate window functions:
– ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
– ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING
– ROWS BETWEEN CURRENT ROW AND CURRENT ROW
– Named windows
• SET AUTOCOMMIT READ autocommits a transaction after a reading query, allowing updating queries to start a multistatement transaction. This feature helps queries avoid out-of-memory conditions by freeing memory occupied by uncommitted transactions.
• Configuration option [engine] enable_reuse_disk_spilling=true enables spilling to disk for reused query plan parts.
• Union flattening at the server, session, and statement levels, which improves query performance.
The following new features were added in Vector 4.2.3:
• Spark-Vector Connector, which lets you interact with a Vector database using Apache Spark.
• Spark-Vector Loader, a command line client utility that lets you load CSV, Parquet, and ORC files through Spark into Vector, using the Spark-Vector Connector.
• Per query profile files can be written to the directory specified on the [server] profile_per_query_dir configuration parameter.
• WITH [NO]MINMAX option on CREATE TABLE lets you create min-max indexes on a subset of columns.
Last modified date: 11/09/2022