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docs-v2/content/shared/influxdb3-write-guides/best-practices/optimize-writes.md

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Use these tips to optimize performance and system overhead when writing data to
{{< product-name >}}.
- [Batch writes](#batch-writes)
- [Sort tags by key](#sort-tags-by-key)
- [Use the coarsest time precision possible](#use-the-coarsest-time-precision-possible)
- [Use gzip compression](#use-gzip-compression)
- [Enable gzip compression in Telegraf](#enable-gzip-compression-in-telegraf)
- [Enable gzip compression in InfluxDB client libraries](#enable-gzip-compression-in-influxdb-client-libraries)
- [Use gzip compression with the InfluxDB API](#use-gzip-compression-with-the-influxdb-api)
- [Synchronize hosts with NTP](#synchronize-hosts-with-ntp)
- [Write multiple data points in one request](#write-multiple-data-points-in-one-request)
- [Pre-process data before writing](#pre-process-data-before-writing)
- [Prerequisites](#prerequisites)
- [Filter data from a batch](#filter-data-from-a-batch)
- [Coerce data types to avoid rejected point errors](#coerce-data-types-to-avoid-rejected-point-errors)
- [Merge lines to optimize memory and bandwidth](#merge-lines-to-optimize-memory-and-bandwidth)
- [Avoid sending duplicate data](#avoid-sending-duplicate-data)
- [Run custom preprocessing code](#run-custom-preprocessing-code)
> [!Note]
> The following tools write to InfluxDB and employ _most_ write optimizations by
> default:
>
> - [Telegraf](/influxdb3/version/write-data/use-telegraf/)
> - InfluxDB client libraries
## Batch writes
Write data in batches to minimize network overhead when writing data to InfluxDB.
> [!Note]
> The optimal batch size is 10,000 lines of line protocol or 10 MBs, whichever
> threshold is met first.
## Sort tags by key
Before writing data points to InfluxDB, sort tags by key in lexicographic order.
_Verify sort results match results from the [Go `bytes.Compare` function](http://golang.org/pkg/bytes/#Compare)._
<!-- pytest.mark.skip -->
```bash
# Line protocol example with unsorted tags
measurement,tagC=therefore,tagE=am,tagA=i,tagD=i,tagB=think fieldKey=fieldValue 1562020262
# Optimized line protocol example with tags sorted by key
measurement,tagA=i,tagB=think,tagC=therefore,tagD=i,tagE=am fieldKey=fieldValue 1562020262
```
## Use the coarsest time precision possible
{{< product-name >}} supports up to nanosecond timestamp precision. However,
if your data isn't collected in nanoseconds, there is no need to write at that precision.
For better performance, use the coarsest timestamp precision you can for your
use case.
By default, {{< product-name >}} attempts to auto-detect the precision of
timestamps in line protocol by identifying what precision would be relatively
close to "now." You can also specify your timestamp precision in your write
request. {{< product-name >}} supports the following timestamp precisions:
- `ns` (nanoseconds)
- `us` (microseconds)
- `ms` (milliseconds)
- `s` (seconds)
## Use gzip compression
Use gzip compression to speed up writes to {{< product-name >}}.
Benchmarks have shown up to a 5x speed improvement when data is compressed.
{{< tabs-wrapper >}}
{{% tabs %}}
[Telegraf](#)
[Client libraries](#)
[InfluxDB API](#)
{{% /tabs %}}
{{% tab-content %}}
### Enable gzip compression in Telegraf
In the `influxdb_v2` output plugin configuration in your `telegraf.conf`, set the
`content_encoding` option to `gzip`:
```toml
[[outputs.influxdb_v2]]
urls = ["https://{{< influxdb/host >}}"]
# ...
content_encoding = "gzip"
```
{{% /tab-content %}}
{{% tab-content %}}
### Enable gzip compression in InfluxDB client libraries
Each [InfluxDB client library](/influxdb3/version/reference/client-libraries/) provides
options for compressing write requests or enforces compression by default.
The method for enabling compression is different for each library.
For specific instructions, see the
[InfluxDB client libraries documentation](/influxdb3/version/reference/client-libraries/).
{{% /tab-content %}}
{{% tab-content %}}
### Use gzip compression with the InfluxDB API
When using the InfluxDB API `/api/v2/write` endpoint to write data,
compress the data with `gzip` and set the `Content-Encoding` header to `gzip`--for example:
{{% influxdb/custom-timestamps %}}
{{% code-placeholders "(AUTH|DATABASE)_(TOKEN|NAME)" %}}
{{% code-callout "Content-Encoding: gzip" "orange" %}}
```bash
echo "mem,host=host1 used_percent=23.43234543 1641024000
mem,host=host2 used_percent=26.81522361 1641027600
mem,host=host1 used_percent=22.52984738 1641031200
mem,host=host2 used_percent=27.18294630 1641034800" | gzip > system.gzip \
curl --request POST "https://{{< influxdb/host >}}/api/v2/write?org=ignored&bucket=DATABASE_NAME" \
--header "Authorization: Token AUTH_TOKEN" \
--header "Content-Type: text/plain; charset=utf-8" \
--header "Content-Encoding: gzip" \
--data-binary @system.gzip
```
{{% /code-callout %}}
{{% /code-placeholders %}}
{{% /influxdb/custom-timestamps %}}
Replace the following:
- {{% code-placeholder-key %}}`DATABASE_NAME`{{% /code-placeholder-key %}}:
the name of the database to write data to
- {{% code-placeholder-key %}}`AUTH_TOKEN`{{% /code-placeholder-key %}}:
your {{< product-name >}} authorization token.
_Store this in a secret store or environment variable to avoid exposing the raw token string._
> [!Note]
> While in beta, {{< product-name >}} does not require an authorization token.
> You can either omit the `Authorization` header or you can provide an
> arbitrary token string.
{{% /tab-content %}}
{{< /tabs-wrapper >}}
## Synchronize hosts with NTP
Use the Network Time Protocol (NTP) to synchronize time between hosts.
If a timestamp isn't included in line protocol, InfluxDB uses its host's local
time (in UTC) to assign timestamps to each point.
If a host's clocks isn't synchronized with NTP, timestamps may be inaccurate.
## Write multiple data points in one request
To write multiple lines in one request, each line of line protocol must be
delimited by a new line (`\n`).
## Pre-process data before writing
Pre-processing data in your write workload can help you avoid
[write failures](/influxdb3/version/write-data/troubleshoot/#troubleshoot-failures)
due to schema conflicts or resource use.
For example, if you have many devices that write to the same table, and some
devices use different data types for the same field, then you might want to
generate an alert or convert field data to fit your schema before you send the
data to InfluxDB.
With [Telegraf](/telegraf/v1/), you can process data from other services and
files and then write it to InfluxDB.
In addition to processing data with Telegraf's included plugins, you can use the
[Execd processor plugin](/telegraf/v1/plugins/#processor-execd) to integrate
your own code and external applications.
The following examples show how to [configure the Telegraf agent](/telegraf/v1/configuration)
and [plugins](/telegraf/v1/plugins/) to optimize writes.
The examples use the [File input plugin](/telegraf/v1/plugins/#input-file) to
read data from a file and use the [InfluxDB v2 output plugin](/telegraf/v1/plugins/#input-influxdb)
to write data to a database, but you can use any input and output plugin.
### Prerequisites
[Install Telegraf](/telegraf/v1/install/) if you haven't already.
### Filter data from a batch
Use Telegraf and metric filtering to filter data before writing it to InfluxDB.
Configure [metric filters](/telegraf/v1/configuration/#filters) to retain or
remove data elements (before processor and aggregator plugins run).
1. Enter the following command to create a Telegraf configuration that parses
system usage data, removes the specified fields and tags, and then writes
the data to InfluxDB:
<!--pytest-codeblocks:cont-->
{{< code-placeholders "DATABASE_NAME|AUTH_TOKEN" >}}
```sh
cat <<EOF >> ./telegraf.conf
[[inputs.cpu]]
# Remove the specified fields from points.
fieldpass = ["usage_system", "usage_idle"]
# Remove the specified tags from points.
tagexclude = ["host"]
[[outputs.influxdb_v2]]
urls = ["http://{{< influxdb/host >}}"]
token = "AUTH_TOKEN"
organization = ""
bucket = "DATABASE_NAME"
EOF
```
{{< /code-placeholders >}}
Replace the following:
- {{% code-placeholder-key %}}`DATABASE_NAME`{{% /code-placeholder-key %}}:
the name of the database to write data to
- {{% code-placeholder-key %}}`AUTH_TOKEN`{{% /code-placeholder-key %}}:
your {{< product-name >}} authorization token.
_Store this in a secret store or environment variable to avoid exposing the raw token string._
> [!Note]
> While in beta, {{< product-name >}} does not require an authorization token.
> For the `token` option, provide an empty or arbitrary token string.
2. To test the input and processor, enter the following command:
<!--pytest-codeblocks:cont-->
```sh
telegraf --test --config telegraf.conf
```
The output is similar to the following.
For each row of input data, the filters pass the metric name, tags,
specified fields, and timestamp.
```text
> cpu,cpu=cpu0 usage_idle=100,usage_system=0 1702067201000000000
...
> cpu,cpu=cpu-total usage_idle=99.80198019802448,usage_system=0.1980198019802045 1702067201000000000
```
### Coerce data types to avoid rejected point errors
Use Telegraf and the [Converter processor plugin](/telegraf/v1/plugins/#processor-converter)
to convert field data types to fit your schema.
For example, if you write the sample data in
[Home sensor sample data](/influxdb3/version/reference/sample-data/#home-sensor-data)
to a database and then try to write the following batch to the same table:
{{% influxdb/custom-timestamps %}}
```text
home,room=Kitchen temp=23.1,hum=36.6,co=22.1 1641063600
home,room=Living\ Room temp=22i,hum=36.4,co=17i 1641067200
home,room=Kitchen temp=22.7,hum=36.5,co=26i 1641067200
```
{{% /influxdb/custom-timestamps %}}
InfluxDB expects `co` to contain an integer value and rejects points with `co`
floating-point decimal (`22.1`) values.
To avoid the error, configure Telegraf to convert fields to the data types in
your schema columns.
The following example converts the `temp`, `hum`, and `co` fields to fit the
[sample data](/influxdb3/version/reference/sample-data/#home-sensor-data) schema:
<!--before-test
```sh
curl -s "https://{{< influxdb/host >}}/api/v2/write?bucket=DATABASE_NAME&precision=s" \
--header "Authorization: Token AUTH_TOKEN" \
--header "Content-type: text/plain; charset=utf-8" \
--header "Accept: application/json" \
--data-binary "
home,room=Kitchen temp=23.1,hum=36.6,co=22i 1641063600
home,room=Living\ Room temp=22.2,hum=36.4,co=17i 1641067200
home,room=Kitchen temp=22.7,hum=36.5,co=26i 1641067200"
```
-->
1. In your terminal, enter the following command to create the sample data file:
<!--pytest-codeblocks:cont-->
```sh
cat <<EOF > ./home.lp
home,room=Kitchen temp=23.1,hum=36.6,co=22.1 1641063600
home,room=Living\ Room temp=22i,hum=36.4,co=17i 1641067200
home,room=Kitchen temp=22.7,hum=36.5,co=26i 1641067200
EOF
```
2. Enter the following command to create a Telegraf configuration that parses
the sample data, converts the field values to the specified data types, and
then writes the data to InfluxDB:
<!--pytest-codeblocks:cont-->
{{< code-placeholders "DATABASE_NAME|AUTH_TOKEN" >}}
```sh
cat <<EOF > ./telegraf.conf
[[inputs.file]]
## For each interval, parse data from files in the list.
files = ["home.lp"]
influx_timestamp_precision = "1s"
precision = "1s"
tagexclude = ["host"]
[[processors.converter]]
[processors.converter.fields]
## A data type and a list of fields to convert to the data type.
float = ["temp", "hum"]
integer = ["co"]
[[outputs.influxdb_v2]]
## InfluxDB v2 API credentials and the database to write to.
urls = ["https://{{< influxdb/host >}}"]
token = "AUTH_TOKEN"
organization = ""
bucket = "DATABASE_NAME"
EOF
```
{{< /code-placeholders >}}
Replace the following:
- {{% code-placeholder-key %}}`DATABASE_NAME`{{% /code-placeholder-key %}}:
the name of the database to write data to
- {{% code-placeholder-key %}}`AUTH_TOKEN`{{% /code-placeholder-key %}}:
your {{< product-name >}} authorization token.
_Store this in a secret store or environment variable to avoid exposing the raw token string._
> [!Note]
> While in beta, {{< product-name >}} does not require an authorization token.
> For the `token` option, provide an empty or arbitrary token string.
3. To test the input and processor, enter the following command:
<!--pytest-codeblocks:cont-->
```bash
telegraf --test --config telegraf.conf
```
Telegraf outputs the following to stdout, and then exits:
<!--pytest-codeblocks:expected-output-->
```
> home,room=Kitchen co=22i,hum=36.6,temp=23.1 1641063600000000000
> home,room=Living\ Room co=17i,hum=36.4,temp=22 1641067200000000000
> home,room=Kitchen co=26i,hum=36.5,temp=22.7 1641067200000000000
```
<!-- hidden-test >
```bash
# Run once and exit.
telegraf --once --config telegraf.conf
```
-->
### Merge lines to optimize memory and bandwidth
Use Telegraf and the [Merge aggregator plugin](/telegraf/v1/plugins/#aggregator-merge)
to merge points that share the same measurement, tag set, and timestamp.
The following example creates sample data for two series (the combination of
table, tag set, and timestamp), and then merges points in each series:
1. In your terminal, enter the following command to create the sample data file
and calculate the number of seconds between the earliest timestamp and _now_.
The command assigns the calculated value to a `grace_duration` variable that
you'll use in the next step.
```bash
cat <<EOF > ./home.lp
home,room=Kitchen temp=23.1 1641063600
home,room=Kitchen hum=36.6 1641063600
home,room=Kitchen co=22i 1641063600
home,room=Living\ Room temp=22.7 1641063600
home,room=Living\ Room hum=36.4 1641063600
home,room=Living\ Room co=17i 1641063600
EOF
grace_duration="$(($(date +%s)-1641063000))s"
```
2. Enter the following command to configure Telegraf to parse the file, merge
the points, and write the data to InfluxDB--specifically, the configuration
sets the following properties:
- `influx_timestamp_precision`: for parsers, specifies the timestamp
precision in the input data
- Optional: `aggregators.merge.grace` extends the duration for merging points.
To ensure the sample data is included, the configuration uses the
calculated variable from the preceding step.
<!--pytest-codeblocks:cont-->
{{< code-placeholders "DATABASE_NAME|AUTH_TOKEN" >}}
```bash
cat <<EOF > ./telegraf.conf
# Parse metrics from a file
[[inputs.file]]
## A list of files to parse during each interval.
files = ["home.lp"]
## The precision of timestamps in your data.
influx_timestamp_precision = "1s"
tagexclude = ["host"]
# Merge separate metrics that share a series key
[[aggregators.merge]]
grace = "$grace_duration"
## If true, drops the original metric.
drop_original = true
# Writes metrics as line protocol to the InfluxDB v2 API
[[outputs.influxdb_v2]]
## InfluxDB v2 API credentials and the database to write data to.
urls = ["https://{{< influxdb/host >}}"]
token = "AUTH_TOKEN"
organization = ""
bucket = "DATABASE_NAME"
EOF
```
{{< /code-placeholders >}}
Replace the following:
- {{% code-placeholder-key %}}`DATABASE_NAME`{{% /code-placeholder-key %}}:
the name of the database to write data to
- {{% code-placeholder-key %}}`AUTH_TOKEN`{{% /code-placeholder-key %}}:
your {{< product-name >}} authorization token.
_Store this in a secret store or environment variable to avoid exposing the raw token string._
> [!Note]
> While in beta, {{< product-name >}} does not require an authorization token.
> For the `token` option, provide an empty or arbitrary token string.
3. To test the input and aggregator, enter the following command:
<!--pytest-codeblocks:cont-->
```bash
telegraf --test --config telegraf.conf
```
Telegraf outputs the following to stdout, and then exits:
<!--pytest-codeblocks:expected-output-->
```
> home,room=Kitchen co=22i,hum=36.6,temp=23.1 1641063600000000000
> home,room=Living\ Room co=17i,hum=36.4,temp=22.7 1641063600000000000
```
<!-- hidden-test >
```bash
# Run once and exit.
telegraf --once --config telegraf.conf
```
-->
### Avoid sending duplicate data
Use Telegraf and the [Dedup processor plugin](/telegraf/v1/plugins/#processor-dedup)
to filter data whose field values are exact repetitions of previous values.
Deduplicating your data can reduce your write payload size and resource usage.
The following example shows how to use Telegraf to remove points that repeat
field values, and then write the data to InfluxDB:
1. In your terminal, enter the following command to create the sample data file
and calculate the number of seconds between the earliest timestamp and _now_.
The command assigns the calculated value to a `dedup_duration` variable that
you'll use in the next step.
```bash
cat <<EOF > ./home.lp
home,room=Kitchen temp=23.1,hum=36.6,co=22i 1641063600
home,room=Living\ Room temp=22.5,hum=36.4,co=17i 1641063600
home,room=Kitchen temp=22.7,hum=36.5,co=26i 1641063605
home,room=Living\ Room temp=22.5,hum=36.4,co=17i 1641063605
home,room=Kitchen temp=23.1,hum=36.6,co=22i 1641063610
home,room=Living\ Room temp=23.0,hum=36.4,co=17i 1641063610
EOF
dedup_duration="$(($(date +%s)-1641063000))s"
```
2. Enter the following command to configure Telegraf to parse the file, drop
duplicate points, and write the data to InfluxDB--specifically, the sample configuration sets the following:
- `influx_timestamp_precision`: for parsers, specifies the timestamp
precision in the input data
- `processors.dedup`: configures the Dedup processor plugin
- Optional: `processors.dedup.dedup_interval`. Points in the range
`dedup_interval` _to now_ are considered for removal.
To ensure the sample data is included, the configuration uses the
calculated variable from the preceding step.
<!--pytest-codeblocks:cont-->
{{< code-placeholders "DATABASE_NAME|AUTH_TOKEN" >}}
```bash
cat <<EOF > ./telegraf.conf
# Parse metrics from a file
[[inputs.file]]
## A list of files to parse during each interval.
files = ["home.lp"]
## The precision of timestamps in your data.
influx_timestamp_precision = "1s"
tagexclude = ["host"]
# Filter metrics that repeat previous field values
[[processors.dedup]]
## Drops duplicates within the specified duration
dedup_interval = "$dedup_duration"
# Writes metrics as line protocol to the InfluxDB v2 API
[[outputs.influxdb_v2]]
## InfluxDB v2 API credentials and the database to write data to.
urls = ["https://{{< influxdb/host >}}"]
token = "AUTH_TOKEN"
organization = ""
bucket = "DATABASE_NAME"
EOF
```
{{< /code-placeholders >}}
Replace the following:
- {{% code-placeholder-key %}}`DATABASE_NAME`{{% /code-placeholder-key %}}:
the name of the database to write data to
- {{% code-placeholder-key %}}`AUTH_TOKEN`{{% /code-placeholder-key %}}:
your {{< product-name >}} authorization token.
_Store this in a secret store or environment variable to avoid exposing the raw token string._
> [!Note]
> While in beta, {{< product-name >}} does not require an authorization token.
> For the `token` option, provide an empty or arbitrary token string.
3. To test the input and processor, enter the following command:
<!--pytest-codeblocks:cont-->
```bash
telegraf --test --config telegraf.conf
```
Telegraf outputs the following to stdout, and then exits:
<!--pytest-codeblocks:expected-output-->
```
> home,room=Kitchen co=22i,hum=36.6,temp=23.1 1641063600000000000
> home,room=Living\ Room co=17i,hum=36.4,temp=22.5 1641063600000000000
> home,room=Kitchen co=26i,hum=36.5,temp=22.7 1641063605000000000
> home,room=Kitchen co=22i,hum=36.6,temp=23.1 1641063610000000000
> home,room=Living\ Room co=17i,hum=36.4,temp=23 1641063610000000000
```
<!-- hidden-test >
```bash
# Run once and exit.
telegraf --once --config telegraf.conf
```
-->
### Run custom preprocessing code
Use Telegraf and the [Execd processor plugin](/telegraf/v1/plugins/#processor-execd)
to execute code external to Telegraf and then write the processed data.
The Execd plugin expects line protocol data in stdin, passes the data to the
configured executable, and then outputs line protocol to stdout.
The following example shows how to use Telegraf to execute Go code for
processing metrics and then write the output to InfluxDB.
The Go `multiplier.go` sample code does the following:
1. Imports `influx` parser and serializer plugins from Telegraf.
2. Parses each line of data into a Telegraf metric.
3. If the metric contains a `count` field, multiplies the field value by `2`;
otherwise, prints a message to stderr and exits.
1. In your editor, enter the following sample code and save the file as `multiplier.go`:
```go
package main
import (
"fmt"
"os"
"github.com/influxdata/telegraf/plugins/parsers/influx"
influxSerializer "github.com/influxdata/telegraf/plugins/serializers/influx"
)
func main() {
parser := influx.NewStreamParser(os.Stdin)
serializer := influxSerializer.Serializer{}
if err := serializer.Init(); err != nil {
fmt.Fprintf(os.Stderr, "serializer init failed: %v\n", err)
os.Exit(1)
}
for {
metric, err := parser.Next()
if err != nil {
if err == influx.EOF {
return // stream ended
}
if parseErr, isParseError := err.(*influx.ParseError); isParseError {
fmt.Fprintf(os.Stderr, "parse ERR %v\n", parseErr)
os.Exit(1)
}
fmt.Fprintf(os.Stderr, "ERR %v\n", err)
os.Exit(1)
}
c, found := metric.GetField("count")
if !found {
fmt.Fprintf(os.Stderr, "metric has no count field\n")
os.Exit(1)
}
switch t := c.(type) {
case float64:
t *= 2
metric.AddField("count", t)
case int64:
t *= 2
metric.AddField("count", t)
default:
fmt.Fprintf(os.Stderr, "count is not an unknown type, it's a %T\n", c)
os.Exit(1)
}
b, err := serializer.Serialize(metric)
if err != nil {
fmt.Fprintf(os.Stderr, "ERR %v\n", err)
os.Exit(1)
}
fmt.Fprint(os.Stdout, string(b))
}
}
```
<!-- hidden-test
```bash
cat <<EOF > ./multiplier.go
package main
import (
"fmt"
"os"
"github.com/influxdata/telegraf/plugins/parsers/influx"
influxSerializer "github.com/influxdata/telegraf/plugins/serializers/influx"
)
func main() {
parser := influx.NewStreamParser(os.Stdin)
serializer := influxSerializer.Serializer{}
if err := serializer.Init(); err != nil {
fmt.Fprintf(os.Stderr, "serializer init failed: %v\n", err)
os.Exit(1)
}
for {
metric, err := parser.Next()
if err != nil {
if err == influx.EOF {
return // stream ended
}
if parseErr, isParseError := err.(*influx.ParseError); isParseError {
fmt.Fprintf(os.Stderr, "parse ERR %v\n", parseErr)
os.Exit(1)
}
fmt.Fprintf(os.Stderr, "ERR %v\n", err)
os.Exit(1)
}
c, found := metric.GetField("count")
if !found {
fmt.Fprintf(os.Stderr, "metric has no count field\n")
os.Exit(1)
}
switch t := c.(type) {
case float64:
t *= 2
metric.AddField("count", t)
case int64:
t *= 2
metric.AddField("count", t)
default:
fmt.Fprintf(os.Stderr, "count is not an unknown type, it's a %T\n", c)
os.Exit(1)
}
b, err := serializer.Serialize(metric)
if err != nil {
fmt.Fprintf(os.Stderr, "ERR %v\n", err)
os.Exit(1)
}
fmt.Fprint(os.Stdout, string(b))
}
}
EOF
```
-->
2. Initialize the module and install dependencies:
<!--pytest-codeblocks:cont-->
```bash
go mod init processlp
go mod tidy
```
3. In your terminal, enter the following command to create the sample data file:
<!--pytest-codeblocks:cont-->
```bash
cat <<EOF > ./home.lp
home,room=Kitchen temp=23.1,count=1 1641063600
home,room=Living\ Room temp=22.7,count=1 1641063600
home,room=Kitchen temp=23.1 1641063601
home,room=Living\ Room temp=22.7 1641063601
EOF
```
4. Enter the following command to configure Telegraf to parse the file, execute
the Go binary, and write the data--specifically, the sample configuration
sets the following:
- `influx_timestamp_precision`: for parsers, specifies the timestamp
precision in the input data
- `processors.execd`: configures the Execd plugin
- `processors.execd.command`: sets the executable and arguments for Execd to run
<!--pytest-codeblocks:cont-->
{{< code-placeholders "DATABASE_NAME|AUTH_TOKEN" >}}
```bash
cat <<EOF > ./telegraf.conf
# Parse metrics from a file
[[inputs.file]]
## A list of files to parse during each interval.
files = ["home.lp"]
## The precision of timestamps in your data.
influx_timestamp_precision = "1s"
tagexclude = ["host"]
# Filter metrics that repeat previous field values
[[processors.execd]]
## A list that contains the executable command and arguments to run as a daemon.
command = ["go", "run", "multiplier.go"]
# Writes metrics as line protocol to the InfluxDB v2 API
[[outputs.influxdb_v2]]
## InfluxDB v2 API credentials and the database to write data to.
urls = ["https://{{< influxdb/host >}}"]
token = "AUTH_TOKEN"
organization = ""
bucket = "DATABASE_NAME"
EOF
```
{{< /code-placeholders >}}
Replace the following:
- {{% code-placeholder-key %}}`DATABASE_NAME`{{% /code-placeholder-key %}}:
the name of the database to write data to
- {{% code-placeholder-key %}}`AUTH_TOKEN`{{% /code-placeholder-key %}}:
your {{< product-name >}} authorization token.
_Store this in a secret store or environment variable to avoid exposing the raw token string._
> [!Note]
> While in beta, {{< product-name >}} does not require an authorization token.
> For the `token` option, provide an empty or arbitrary token string.
5. To test the input and processor, enter the following command:
<!--pytest-codeblocks:cont-->
```bash
telegraf --test --config telegraf.conf
```
Telegraf outputs the following to stdout, and then exits:
<!--pytest-codeblocks:expected-output-->
```
> home,room=Kitchen count=2,temp=23.1 1641063600000000000
> home,room=Living\ Room count=2,temp=22.7 1641063600000000000
```
<!-- hidden-test >
```bash
# Run once and exit.
telegraf --once --config telegraf.conf
```
-->
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