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Adding upstream version 1.34.4.

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Signed-off-by: Daniel Baumann <daniel@debian.org>
This commit is contained in:
Daniel Baumann 2025-05-24 07:26:29 +02:00
parent e393c3af3f
commit 4978089aab
Signed by: daniel
GPG key ID: FBB4F0E80A80222F
4963 changed files with 677545 additions and 0 deletions
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46
plugins/processors/starlark/testdata/json_nested.star vendored Normal file
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#
# This code assumes the value parser with data_type='string' is used
# in the input collecting the JSON data. The entire JSON obj/doc will
# be set to a Field named `value` with which this code will work.
# JSON:
# ```
# {
# "fields": {
# "LogEndOffset": 339238,
# "LogStartOffset": 339238,
# "NumLogSegments": 1,
# "Size": 0,
# "UnderReplicatedPartitions": 0
# },
# "name": "partition",
# "tags": {
# "host": "CUD1-001559",
# "jolokia_agent_url": "http://localhost:7777/jolokia",
# "partition": "1",
# "topic": "qa-kafka-connect-logs"
# },
# "timestamp": 1591124461
# } ```
#
# Example Input:
# json value="[{\"fields\": {\"LogEndOffset\": 339238, \"LogStartOffset\": 339238, \"NumLogSegments\": 1, \"Size\": 0, \"UnderReplicatedPartitions\": 0}, \"name\": \"partition\", \"tags\": {\"host\": \"CUD1-001559\", \"jolokia_agent_url\": \"http://localhost:7777/jolokia\", \"partition\": \"1\", \"topic\": \"qa-kafka-connect-logs\"}, \"timestamp\": 1591124461}]"
# Example Output:
# partition,host=CUD1-001559,jolokia_agent_url=http://localhost:7777/jolokia,partition=1,topic=qa-kafka-connect-logs LogEndOffset=339238i,LogStartOffset=339238i,NumLogSegments=1i,Size=0i,UnderReplicatedPartitions=0i 1591124461000000000
load("json.star", "json")
def apply(metric):
j_list = json.decode(metric.fields.get('value')) # input JSON may be an arrow of objects
metrics = []
for obj in j_list:
new_metric = Metric("partition") # We want a new InfluxDB/Telegraf metric each iteration
for tag in obj["tags"].items(): # 4 Tags to iterate through
new_metric.tags[str(tag[0])] = tag[1]
for field in obj["fields"].items(): # 5 Fields to iterate through
new_metric.fields[str(field[0])] = field[1]
new_metric.time = int(obj["timestamp"] * 1e9)
metrics.append(new_metric)
return metrics