Load balancing measurement function

Before you perform operations to implement load balancing on your distributed system, you must measure the load balancing degree of the system in an accurate manner. This topic describes the syntax of the load balancing measurement function. This topic also provides examples on how to use the function.

Background information

The sample log for which the load balancing measurement function is used contains the following indexed fields: cluster ID, server ID, time, CPU load, memory load, and network bandwidth load. For more information, see Create indexes.

Sample log:

{"cluster_id":"C001","cpu_load":"0.1","network_load":"0.6","ram_load":"0.7","server_id":"S001","time_period":"2024-01-01 00:00:00"}
{"cluster_id":"C001","cpu_load":"0.2","network_load":"0.5","ram_load":"0.8","server_id":"S002","time_period":"2024-01-01 00:01:00"}
{"cluster_id":"C001","cpu_load":"0.1","network_load":"0.6","ram_load":"0.7","server_id":"S001","time_period":"2024-01-01 00:02:00"}
{"cluster_id":"C001","cpu_load":"0.2","network_load":"0.5","ram_load":"0.8","server_id":"S002","time_period":"2024-01-01 00:03:00"}
{"cluster_id":"C001","cpu_load":"0.1","network_load":"0.6","ram_load":"0.7","server_id":"S001","time_period":"2024-01-01 00:04:00"}
{"cluster_id":"C001","cpu_load":"0.2","network_load":"0.5","ram_load":"0.8","server_id":"S002","time_period":"2024-01-01 00:05:00"}
{"cluster_id":"C001","cpu_load":"0.1","network_load":"0.6","ram_load":"0.7","server_id":"S001","time_period":"2024-01-01 00:06:00"}
{"cluster_id":"C001","cpu_load":"0.2","network_load":"0.5","ram_load":"0.8","server_id":"S002","time_period":"2024-01-01 00:07:00"}
{"cluster_id":"C001","cpu_load":"0.1","network_load":"0.6","ram_load":"0.7","server_id":"S001","time_period":"2024-01-01 00:08:00"}
{"cluster_id":"C001","cpu_load":"0.2","network_load":"0.5","ram_load":"0.8","server_id":"S002","time_period":"2024-01-01 00:09:00"}

Function	Syntax	Description	Data type of the return value
how_balanced function	how_balanced(array(array(double)) load_matrix)	Measures the load balancing degree of your distributed system. You must use this function together with the array_agg function. For more information, see array_agg function. The return value indicates the load balancing degree. Valid values: `(0,1]`. A value that is closer to 1 indicates a high degree of load balancing. A value of 1 indicates full load balancing.	double

how_balanced function

The how_balanced function measures the load balancing degree of your distributed system. You must use this function together with the array_agg function. For more information, see array_agg function.

double how_balanced(array(array(double)) load_matrix)

Parameter	Description
`load_matrix`	The load matrix. Each row specifies the load time sequence vector of a server.

Example

Query statement

* | with server_time_series as
(
    select cluster_id,
        server_id,
        array_agg(to_unixtime(date_parse(time_period, '%Y-%m-%d %H:%i:%s'))) as time_periods,
        array_agg(cpu_load + ram_load + network_load) as metric_values
    from log
    where time_period >= '2024-01-01 00:00:00'
      and time_period < '2024-01-02 00:00:00'
    group by cluster_id, server_id
),

imputed_server_series as
(
    select cluster_id,
        server_id,
        ts_fill_missing(
            time_periods,
            metric_values,
            to_unixtime(date_parse('2024-01-01 00:00:00', '%Y-%m-%d %H:%i:%s')),
            to_unixtime(date_parse('2024-01-02 00:00:00', '%Y-%m-%d %H:%i:%s')),
            '1 minute', 'value=0') as imputed_time_series
    from server_time_series
)

select cluster_id,
    how_balanced(array_agg(imputed_time_series[2])) as balance
from imputed_server_series
group by cluster_id

Query and analysis results
balance indicates the load balancing degree. Valid values: (0,1]. A value that is closer to 1 indicates a high degree of load balancing. A value of 1 indicates full load balancing.
cluster_id
balance
G1
0.5

cluster_id	balance
G1	0.5