AnalyticDB for PostgreSQL - New Minor Version Released and SQL Diagnostics and Optimization Enhanced
Oct 13 2021AnalyticDB for PostgreSQL
Target customers: all users of AnalyticDB for PostgreSQL in version 18.104.22.168 or later. Features released: The new minor version provides the following features: New features - Auto-merge is supported for append-optimized row-oriented and append-optimized column-oriented tables. - Column-based sorting acceleration is supported for scenarios where data is incrementally updated. - The query performance of the execution engine is improved. - The maximum number of connections is increased to up to 950. - Idle connections are automatically closed. - Auto-analyze and auto-vacuum are supported for the multi-coordinator architecture. - Real-time materialized views are supported for INSERT ON CONFLICT DO UPDATE and COPY ON CONFLICT DO UPDATE statements. Fixed issues - The issue that real-time materialized views fail to refresh in a multi-coordinator architecture is fixed. - The issue that real-time materialized views cannot support replicated tables is fixed. - The issue that real-time materialized views cannot support UPSERT statements is fixed. - The issue that the column name cannot contain totalrows or totaldeadrows is fixed. - The issue that the data type cannot be converted from INT96 to TIMESTAMP in Parquet-formatted OSS foreign tables is fixed. - The issue that causes archiving exceptions is fixed. Archiving exceptions may occur because archiving programs are missing or Python modules fail to be imported after a primary/secondary switchover. - The issue that causes memory leaks is fixed. Memory leaks may occur if data is accessed or a source file is changed while OSS foreign tables are being scanned. Default configuration changes - By default, the PL/Java feature is disabled. The SQL diagnostics and optimization feature offers the following enhancements: - View slow SQL queries You can analyze SQL queries executed within a specific time range, view execution plan details, and identify root causes of slow SQL queries. - SQL distribution statistics You can view the proportions of SQL queries by using dimensions such as databases, SQL types, SQL execution durations, and users within a specific time range.