# InfluxDB high CPU usage after writing
**URL:** https://community.influxdata.com/t/influxdb-high-cpu-usage-after-writing/33887
**Category:** InfluxDB 2
**Tags:** influxdb, performance
**Created:** [April 10, 2024, 2:34pm UTC](https://community.influxdata.com/t/influxdb-high-cpu-usage-after-writing/33887 "2024-04-10T14:34:13Z")
**Posts on this page:** 1
**Page:** 1
### Author:  [@matvey](https://community.influxdata.com/u/matvey)
#### Post date: [April 10, 2024, 2:34pm UTC](https://community.influxdata.com/t/influxdb-high-cpu-usage-after-writing/33887/1 "2024-04-10T14:34:13Z")
Hello to everyone!
**Input data:**
- InfluxDB 2.7.0 working in docker container.
- DB has write and read operations from different services and telegraf.
- Target bucket with retention for 7 days.
Everything works fine unit I want to write some more data.
**Problem**
After writing 675 points at once by line protocol (this write operation does not differ from stable service work):
format: measurement \_field= epoch\_seconds
```auto
data 7554e18b-f031-4777-a427-24301c7a0989=30.0 1712666633
data 4279dbf1-e230-419f-99b7-7821f3ceb68a=50.0 1712666633
data 16516605-7df0-4c82-8826-39e70bffe445=5.0 1712666633
data 50951fdf-0730-4e96-ba8c-69feabfc3167=10.0 1712666633
data afca57d5-a4cc-4bf8-8e2f-973dbfc75b47=1.0 1712666633
// more data
```
I have high CPU usage % for half an hour - 140-160%, usual is less than 1%.
You can see CPU usage on image:
> **Result of \`go tool pprof http://\:8086/debug/pprof/profile?seconds=120\` and \`top 25\`**
>
> ```auto
> flat flat% sum% cum cum%
> 12.27s 7.19% 7.19% 14.16s 8.30% runtime.findObject
> 10.09s 5.91% 13.10% 73.91s 43.30% runtime.mallocgc
> 9.90s 5.80% 18.90% 12.49s 7.32% runtime.step
> 9.52s 5.58% 24.48% 26.84s 15.73% runtime.pcvalue
> 7.47s 4.38% 28.86% 40.46s 23.71% runtime.scanobject
> 7.07s 4.14% 33.00% 15.64s 9.16% runtime.greyobject
> 6.89s 4.04% 37.03% 38.61s 22.62% runtime.gentraceback
> 6.61s 3.87% 40.91% 6.80s 3.98% runtime.pageIndexOf (inline)
> 4.23s 2.48% 43.39% 4.23s 2.48% runtime.nextFreeFast (inline)
> 3.36s 1.97% 45.35% 3.36s 1.97% runtime.(*moduledata).textAddr
> 2.76s 1.62% 46.97% 2.98s 1.75% runtime.findfunc
> 2.74s 1.61% 48.58% 6.64s 3.89% runtime.heapBitsSetType
> 2.74s 1.61% 50.18% 2.74s 1.61% runtime.memclrNoHeapPointers
> 2.59s 1.52% 51.70% 2.59s 1.52% runtime.readvarint (inline)
> 2.51s 1.47% 53.17% 2.65s 1.55% runtime.writeHeapBits.flush
> 2.40s 1.41% 54.58% 2.48s 1.45% runtime.heapBitsForAddr
> 2.27s 1.33% 55.91% 7.86s 4.61% github.com/google/flatbuffers/go.(*Builder).WriteVtable
> 1.95s 1.14% 57.05% 1.96s 1.15% runtime.(*fixalloc).alloc
> 1.85s 1.08% 58.13% 2.84s 1.66% github.com/influxdata/flux/internal/execute/groupkey.groupKeyLess
> 1.84s 1.08% 59.21% 3.14s 1.84% runtime.(*sweepLocked).sweep
> 1.46s 0.86% 60.07% 17.48s 10.24% github.com/google/flatbuffers/go.(*Builder).Prep
> 1.38s 0.81% 60.87% 4.74s 2.78% runtime.funcInfo.entry (partial-inline)
> 1.37s 0.8% 61.68% 5.29s 3.10% github.com/influxdata/flux/values.(*object).Range
> 1.17s 0.69% 62.36% 1.37s 0.8% runtime.markrootSpans
> 1.16s 0.68% 63.04% 1.17s 0.69% runtime.spanOf (inline)
>
> ```
What is wrong with influxdb and how can i reduce CPU usage?
Possible crutch solution:
Writing data by parts during one hour.
For example 50 points for each 5 minutes.
In this case i have some local CPU peaks 50-100% for 1-2 minutes - this is acceptable.