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The segment_* tables contain memory allocation statistics for the Greenplum Database segment instances. This tracks the amount of memory consumed by all postgres processes of a particular segment instance, and the remaining amount of memory available to a segment as per the settings configured by the currently active resource management scheme (resource group-based or resource queue-based). See the Greenplum Database Administrator Guide for more information about resource management schemes.
There are three segment tables, all having the same columns:
- segment_now is an external table whose data files are stored in $MASTER_DATA_DIRECTORY/gpperfmon/data. Current memory allocation data is stored in segment_now during the period between data collection from the gpperfmon agents and automatic commitment to the segment_history table.
- segment_tail is an external table whose data files are stored in $MASTER_DATA_DIRECTORY/gpperfmon/data. This is a transitional table for memory allocation data that has been cleared from segment_now but has not yet been committed to segment_history. It typically only contains a few minutes worth of data.
- segment_history is a regular table that stores historical memory allocation metrics. It is pre-partitioned into monthly partitions. Partitions are automatically added in two month increments as needed.
A particular segment instance is identified by its hostname and dbid (the unique segment identifier as per the gp_segment_configuration system catalog table).
(without time zone)
|The time the row was created.|
|dbid||int||The segment ID (dbid from gp_segment_configuration).|
|hostname||charvar(64)||The segment hostname.|
|dynamic_memory_used||bigint||The amount of dynamic memory (in bytes) allocated to query processes running on this segment.|
|dynamic_memory_available||bigint||The amount of additional dynamic memory (in bytes) that the segment can request before reaching the limit set by the currently active resource management scheme (resource group-based or resource queue-based).|
See also the views memory_info and dynamic_memory_info for aggregated memory allocation and utilization by host.