Job Usage Calculation

The raw job usage factor for an association is defined as the sum of products of number of nodes used (nnodes) and time elapsed (t_elapsed). To calculate the raw usage for a given association U:

\(U = sum(nnodes \times t\_elapsed)\)

flux-accounting keeps track of job usage in a table according to two properties that are set when the database is first created: PriorityDecayHalfLife and PriorityUsageResetPeriod. Each of these parameters represent a number of weeks by which to hold usage factors up to the time period where jobs no longer play a factor in calculating a usage factor. If these options aren't specified, the table defaults to 4 usage columns, each which represent one week's worth of jobs.

The job usage factor table stores past job usage factors per association. When an association is first added to the association table, they are also added to job usage factor table.

The value of PriorityDecayHalfLife determines the amount of time that represents one "usage period" of jobs. flux-accounting filters out its jobs table and retrieves an association's jobs that have completed in the usage period.

As time goes on and usage periods get older, their raw usage value has a decay factor \(D\) (0.5) applied to them before they are added to the user's current raw usage factor.

\(U_{past} = (D \times U_{last\_period}) + (D \times D \times U_{period-2}) + ...\)

After the current usage factor is calculated, it is written to the first usage bin in the job usage factor table along with the other, older factors. The oldest factor then gets removed from the table since it is no longer needed.

An example

Let's say an association has the following job records from the most recent PriorityDecayHalfLife:

   UserID Username  JobID         T_Submit            T_Run       T_Inactive  Nodes                                                                               R
0    1002     1002    102 1605633403.22141 1605635403.22141 1605637403.22141      2  {"version":1,"execution": {"R_lite":[{"rank":"0","children": {"core": "0"}}]}}
1    1002     1002    103 1605633403.22206 1605635403.22206 1605637403.22206      2  {"version":1,"execution": {"R_lite":[{"rank":"0","children": {"core": "0"}}]}}
2    1002     1002    104 1605633403.22285 1605635403.22286 1605637403.22286      2  {"version":1,"execution": {"R_lite":[{"rank":"0","children": {"core": "0"}}]}}
3    1002     1002    105 1605633403.22347 1605635403.22348 1605637403.22348      1  {"version":1,"execution": {"R_lite":[{"rank":"0","children": {"core": "0"}}]}}
4    1002     1002    106 1605633403.22416 1605635403.22416 1605637403.22416      1  {"version":1,"execution": {"R_lite":[{"rank":"0","children": {"core": "0"}}]}}

total nodes used: 8

total time elapsed: 10000.0

\(U_{user1002\_current}\) is calculated as:

\(U_{user1002\_current} = (2 \times 2000) + (2 \times 2000) + (2 \times 2000) + (1 \times 2000) + (1 \times 2000)\)

\(U_{user1002\_current} = 4000 + 4000 + 4000 + 2000 + 2000\)

\(U_{user1002\_current} = 16000\)

And the association's past job usage factors (each one represents a PriorityDecayHalfLife period up to the PriorityUsageResetPeriod) consists of the following:

   username bank  usage_factor_period_0  usage_factor_period_1  usage_factor_period_2  usage_factor_period_3
0  user1002    C               128.0000               64.00000               64.0000               16.00000

The past usage factors have the decay factor applied to them: [64.0, 16.0, 8.0, 1.0]

\(U_{user1002\_past} = 64.0 + 16.0 + 8.0 + 1.0 = 89\)

\(U_{user1002\_historical} = U_{user1002\_current} + U_{user1002\_past} = 16000.0 + 89.0 = 16089.0\)

\(U_{user1002}\)'s job usage value now becomes \(16089.0\), which takes into account both their most recent and historical job usage.

Viewing Breakdowns of Historical Job Usage

Since an association's historical job usage (i.e. the value reported in the job_usage column) is comprised of potentially multiple usage factors that make up an association's job usage value, it would be useful to see how this value is calculated. The view-user command offers a -J/--job-usage optional argument, which will return all of the association's job usage columns that make up their historical job usage value:

$ flux account view-user --parsable -J moussa
username | userid | bank     | usage_factor_period_0 | usage_factor_period_1 | usage_factor_period_2 | usage_factor_period_3
---------+--------+----------+-----------------------+-----------------------+-----------------------+----------------------
moussa   | 12345  | A        | 100.0                 | 243.5                 | 8.7                   | 0.0

Resetting the usage for a bank

The job usage value for a bank (and all of the users under that bank) can be reset with the flux-account-clear-usage(1) command. This will allow you to quickly clear any amount of recently accrued usage, which, on a high-traffic system, can ultimately bump up its users' fair-share values after the entire hierarchy's job usage and fair-share values are updated.

An optional timestamp can also be specified when running this command to tell flux-accounting to only consider jobs newer than said timestamp with the --ignore-older-than optional argument. By default, the clear-usage command will notify any future job usage updates to ignore jobs submitted under that bank older than when the command was issued.

Calculating job usage arbitrarily

flux-accounting also offers a way to report job usage different from displaying a historical job usage value that factors in job decay. view-usage-report can generate a job usage report for users, banks, or associations that can be filtered by start/end dates, how job usage is reported (e.g. by second, minute, or hour) and/or how jobs are binned. Job usage reports are sent to stdout upon completion and is a quick way to look at job usage on a system.

Examples

By default, usage is grouped by association:

$ flux account view-usage-report
association(nodesec)              total
A:50001                          540.00
A:50002                          420.00
B:50003                          300.00
TOTAL                           1260.00

But can also be grouped by user or bank:

$ flux account view-usage-report --report-type byuser
user(nodesec)                     total
50001                            540.00
50002                            420.00
50003                            300.00
TOTAL                           1260.00

$ flux account view-usage-report --report-type bybank
bank(nodesec)                     total
A                                960.00
B                                300.00
TOTAL                           1260.00

How usage is calculated can also be customized:

$ flux account view-usage-report --time-unit hour
association(nodehour)             total
A:50001                            0.15
A:50002                            0.12
B:50003                            0.08
TOTAL                              0.35

Job size bins can also be created to group jobs by their sizes:

$ flux account view-usage-report --job-size-bins=1,2,3,4
association(nodesec)                 1+             2+             3+             4+
A:50001                          180.00         120.00           0.00         240.00
TOTAL                            180.00         120.00           0.00         240.00