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Repository View THROUGHPUT_ALL

Question & Answer


Question

Repository View THROUGHPUT_ALL

Answer

Usage

Throughput_all provides a global view of resource consumption by a database. Common uses of this data include

  • Detecting performance problems by watching for excess consumption of specific resources
  • Tracking how much work is being accomplished by a database

Source

The data in throughput_all comes from the table function mon_get_service_subclass.  Data is aggregated across all service classes, including the system service class.

Columns

As with all repository views, the columns marked Y in the “Delta” column are actually two columns.  For example, the metric described here as “rows_read” is actually a pair of columns “rows_read” which is a counter of how many rows have been read by activities since the data server was activated and “rows_read_delta”, which tells how many rows have been read by activities in the collection interval.  For most purposes, the _delta version of the metrics is the most useful.  The raw counter version is provided for completeness.

Column Name

Delta

Type

Description

dbconn_int

n

integer

 

dbconn_id

n

varchar(255)

 

prev_collected

n

timestamp

 

collected

n

timestamp

 

delta_msec

n

bigint

 

row_id

n

char(5)

This column always contains the string “(all)”

total_cpu_usec

Y

bigint

Microseconds of CPU time consumed by the data server.  Divide by 1,000,000 to scale this as seconds.

CPU consumption is a good indication of how much work is being done.  All activities, including overhead such as compiling queries and utility work are reflected in CPU consumption.  Inefficiencies that increase the cost of doing business, such as excessive recompilation or lock contention can sometimes be seen by observing that CPU consumption has risen disproportionately to the amount of useful work that is being accomplished.

act_completed_total

Y

bigint

Activities completed by the data server.

Activities typically correspond to a query.

The number of activities completed is a measure of work accomplished.

rows_read

Y

bigint

Rows read is a good indication of how much work is being done by queries.  Non-query work such as utilities and overhead for internal activities of the data server is largely excluded from rows read.  So it is a better measure than CPU time for evaluating how much useful work is being accomplished.

rows_modified

Y

bigint

Rows modified includes updates and deletes of table data.  Modifying data is much more expensive than reading it.

rows_returned

Y

bigint

This is the number of rows returned to the client by queries.  Excessive amounts of data returned to the client can indicate a run-away query (cross product, missing filters) or abuse (people in the process of making unauthorized copies of the data) or even bad practices such as mis-guided attempts to pull large portions of the data into a spreadsheet or an application for post processing that could be better done inside the server.

logical_reads

Y

bigint

 

direct_reads

Y

bigint

 

direct_writes

Y

bigint

 

total_sorts

Y

bigint

 

total_app_commits

Y

bigint

 

total_commit_time

Y

bigint

 

total_app_rollbacks

Y

bigint

 

total_section_time

Y

bigint

 

total_routine_time

Y

bigint

 

pool_read_time

Y

bigint

msec

pool_write_time

Y

bigint

msec

direct_read_time

Y

bigint

msec

direct_write_time

Y

bigint

msec

total_section_sort_time

Y

bigint

 

wlm_queue_time_total

Y

bigint

 

lock_wait_time

Y

bigint

 

log_buffer_wait_time

Y

bigint

 

log_disk_wait_time

Y

bigint

 

total_compile_proc_time

Y

bigint

 

total_implicit_compile_proc_time

Y

bigint

 

lock_waits

Y

bigint

 

lock_timeouts

Y

bigint

 

lock_escals

Y

bigint

 

deadlocks

Y

bigint

 

agent_wait_time

Y

bigint

 

lock_wait_time_global

Y

bigint

 

tcpip_wait_time

Y

bigint

 

ipc_wait_time

Y

bigint

 

audit_subsystem_wait_time

Y

bigint

 

audit_file_wrt_wait_time

Y

bigint

 

diaglog_write_wait_time

Y

bigint

 

evmon_wait_time

Y

bigint

 

total_extended_latch_wait_time

Y

bigint

total extended latch wait time

prefetch_wait_time

Y

bigint

 

comm_exit_wait_time

Y

bigint

 

ida_wait_time

Y

bigint

 

cf_wait_time

Y

bigint

 

reclaim_wait_time

Y

bigint

 

spcmapg_reclaim_wait_time

Y

bigint

spacemappage_reclaim_wait_time

total_rtn_u_code_proc_time

Y

bigint

total_rountine_user_code_proc_time

total_section_proc_time

Y

bigint

 

total_sect_sort_proc_time

Y

bigint

total_section_sort_proc_time

total_col_proc_time

Y

bigint

 

total_commit_proc_time

Y

bigint

 

total_rollback_proc_time

Y

bigint

 

total_runstats_proc_time

Y

bigint

 

total_reorg_proc_time

Y

bigint

 

total_load_proc_time

Y

bigint

 

total_backup_proc_time

Y

bigint

 

total_idx_build_proc_time

Y

bigint

total_index_build_proc_time

total_con_req_prc_time

Y

bigint

total_connect_request_proc_time

total_con_auth_prc_time

Y

bigint

total_connect_authentication_proc_time

client_idle_wait_time

Y

bigint

 

total_rqst_time

Y

bigint

 

total_wait_time

Y

bigint

 

sum_sql_execution_time

Y

bigint

 

sum_nonsql_proc_time

Y

bigint

 

sum_io_time

Y

bigint

 

local_lock_wait_time

Y

bigint

 

other_wait_time

Y

bigint

 

total_act_time

    Y

bigint

The total amount of time spent executing activities. Unit: msec

act_aborted_total

    Y

bigint

The total number of coordinator activities at any nesting level that completed with errors

total_compilations

    Y

bigint

 

sort_overflows

    Y

bigint

 

physical_reads

    Y

bigint

 

fed_wait_time

    Y

bigint

federation only, supported from DB2 V11.1

fed_rows_deleted

    Y

bigint

federation only, supported from DB2 V11.1

fed_rows_inserted

    Y

bigint

federation only, supported from DB2 V11.1

fed_rows_updated

    Y

bigint

federation only, supported from DB2 V11.1

fed_rows_read

    Y

bigint

federation only, supported from DB2 V11.1

fed_waits_total

    Y

bigint

federation only, supported from DB2 V11.1

 

Example --

Report on Resource Consumption(CPU, I/O, Average activity time) by hour for specific monitor database:

select date(collected) as date, hour(collected) as time, sum(total_cpu_usec_delta) / 1000000.0 as cpu_sec, sum(logical_reads) as logical_reads, sum(physical_reads) as physical_reads, sum(total_act_time) / (sum(act_aborted_total) + sum(act_completed_total)) as avg_activity_time_msec 

from ibm_dsm_views.throughput_all

where dbconn_id='irww' and prev_collected >= '2018-01-04-00.00.00.000000' and collected < '2018-01-05-00.00.00.000000'

group by date(collected), hour(collected)

order by date, time;

 

Sample Result --

DATE                     TIME             CPU_SEC                    LOGICAL_READS        PHYSICAL_READS       AVG_ACTIVITY_TIME
------------------- ----------- --------------------------------- -------------------- -------------------------- ----------------------------

01/04/2018           2                    16.01750100000              1395280                    21813                            506
01/04/2018           3                    62.76864500000             17924925                   94927                            586
01/04/2018           4                    63.24018500000             36289426                 104054                            572
01/04/2018           5                    59.46574100000             53523267                 114576                            574
01/04/2018           6                    60.68373900000             70625195                 122382                            573
01/04/2018           7                    38.22526400000             51219759                   73962                            601
01/04/2018           8                   129.37073900000            104745837               162113                            605
01/04/2018           9                    53.99299400000            101849283                139136                            604
01/04/2018          10                    59.45694100000            141486943               168374                            597
01/04/2018          11                    33.68107800000             90659370                  99652                            567

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Document Information

Modified date:
31 December 2019

UID

ibm11166350