128 lines
5.0 KiB
TOML
128 lines
5.0 KiB
TOML
# This is a configuration file for the InfluxDB benchmarking tool.
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# High level stats for the benchmark run will be reported to this log file.
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log_file = "benchmark.log"
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# Output summary stats after each block of this number of points has been posted.
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output_after_count = 10000
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# Stats for the benchmark run will be reported to this InfluxDB server. Track it over time, friend.
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[stats_server]
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connection_string = "localhost:8086"
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database = "reports"
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user = "user"
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password = "pass"
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is_secure = false
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skip_verify = false
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timeout = "10s"
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# A regular database, user, and password to read and write data on the cluster being benchmarked.
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[cluster_credentials]
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database = "benchmark"
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user = "paul"
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password = "pass"
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[load_settings]
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# The benchmarker will make this many connections per server listed in servers.
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concurrent_connections = 100
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# If you comment out this setting, load will be simulated for as long
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# as the program runs. This is the number of times each load definition will be
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# run for writes. Queries happen on intervals for as long as the benchmark is running.
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runs_per_load_definition = 10000
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[[servers]]
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connection_string = "localhost:8086"
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is_secure = false
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skip_verify = false
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timeout = "10s"
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# Load definitions describe the reads and writes that you want to simulate.
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# The connections take writes from the load definitions as they're sent out.
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# You can define multiple load definitions that will run in parallel.
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[[load_definitions]]
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# The name is used only for reporting purposes. Response times and point counts
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# will be reported to:
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# <name>.ok
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# <name>.fail
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# The fail time series will contain the error that was returned by the go library.
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name = "write_10_series"
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# For load definitions that will be writing many hundreds of thousands of points
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# it may be more desirable to do some sampling from successful writes. If you
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# comment out the following line you'll get the repsonse time from every 100th
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# write reqeust reported. All failures will still be reported.
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# report_sampling_interval = 100
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# If you're doing sampling you'll want to report some percentiles and the max response
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# times in some window of time. In addition to the sampled report stream you can get
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# percentiles using these two variables. They would produce these series in the
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# reporting dataabase:
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# <name>.percentiles.90, <name>.percentiles.95, <name>.percentiles.99, <name>.percentiles.max
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# percentiles = [90.0, 95.0, 99.0]
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# percentile_time_interval = "10s"
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# series name will start with this string
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base_series_name = "some_series"
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# the number of time series to create
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series_count = 100
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# write settings define write load that will be run against the server
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[load_definitions.write_settings]
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# the number of series that will be in each POST request. if less than series
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# count then multiple posts will be made on each
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batch_series_size = 10
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# the number of points per series that will be in each POST
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batch_points_size = 100
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# time to wait between each POST request on each connection.
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# can be like 10u (microseconds), 10ms, 10s
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delay_between_posts = "0s"
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# each series in this load definition can have multiple int, string, bool, or float columns.
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[[load_definitions.int_columns]]
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name = "value"
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# int values will be random in [0, max_value)
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max_value = 10
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# bool values will be randomly true or false
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[[load_definitions.bool_columns]]
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name = "some_bool"
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# floats will be a random values in [0, 1.0)
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[[load_definitions.float_columns]]
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name = "some_other_val"
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[[load_definitions.string_columns]]
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name = "type"
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# values are potential column values. Each point will have one of these randomly selected
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values = ["click", "open", "view", "delete"]
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# if you want to simulate random string values (i.e. many possible unique strings)
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# leave 'values' out and use this argument. Random strings of that lenght will be generated
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# random_length = 50
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# multiple queries can be run against the server at the same time
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# the writes are happening.
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[[load_definitions.queries]]
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# name is for reporting purposes only. every successful query response time will get reported to:
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# <load definition name>.query.<name>.ok
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# <load definition name>.query.<name>.fail
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name = "count"
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# Using quer_start and query_end will execute against each time series this load definition
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# creates. The series names will be filled in automatically. This example will execute this
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# query against all 10 series every 10 seconds.
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query_start = "select count(value) from "
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query_end = " where time > now() - 30s"
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# queries run periodically based on this setting
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perform_every = "10s"
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[[load_definitions.queries]]
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name = "select_last_point_from_all"
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# The other option is to use full_query. This is useful for specific queries you want
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# to test out like selecting against a regex. This query won't be modified and it will
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# be executed once for every interval (regardless of how many series the load definition creates)
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full_query = "select * from /.*/ limit 1"
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perform_every = "5s"
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