Getting unexpected poor performance in influxDB with 17,280,000 records
I have the following setting:
I expect data from a combined sensor at a rate of 200/s. The record consists of acceleration data (a.X, a.Y) and GPS- data (Lat, Lon). In addition there is data from two force sensors, giving data each from two force components (Fle, Fri).
I set the timestamp of the records while writing to InfluxDB, because it is not sure, that the latency of data is always constant. For testing purpose I set the starttime 24 hours in the past and increment the timestamp with everey record with 5 milliseconds. This means, I write 12,280,000 records to the freshly declared bucket. This takes a lot of time, but is faster than realtime (this means, I write more than 200 records/s). The python code is shown below:
Getting unexpected poor performance in influxDB with 17,280,000 records
I have the following setting:
I expect data from a combined sensor at a rate of 200/s. The record consists of acceleration data (a.X, a.Y) and GPS- data (Lat, Lon). In addition there is data from two force sensors, giving data each from two force components (Fle, Fri).
I set the timestamp of the records while writing to InfluxDB, because it is not sure, that the latency of data is always constant. For testing purpose I set the starttime 24 hours in the past and increment the timestamp with everey record with 5 milliseconds. This means, I write 12,280,000 records to the freshly declared bucket. This takes a lot of time, but is faster than realtime (this means, I write more than 200 records/s). The python code is shown below:
Getting unexpected poor performance in influxDB with 17,280,000 records
I have the following setting:
I expect data from a combined sensor at a rate of 200/s. The record consists of acceleration data (a.X, a.Y) and GPS- data (Lat, Lon). In addition there is data from two force sensors, giving data each from two force components (Fle, Fri).
I set the timestamp of the records while writing to InfluxDB, because it is not sure, that the latency of data is always constant. For testing purpose I set the starttime 24 hours in the past and increment the timestamp with everey record with 5 milliseconds. This means, I write 12,280,000 records to the freshly declared bucket. This takes a lot of time, but is faster than realtime (this means, I write more than 200 records/s). The python code is shown below: