fix(reduce transform): surround invalid path segments with quotes

[pront]

Closes: #21165

Related PR: #21067.

Summary

• Path segments which contain special characters need to be quoted.
• The fields iterator used to only escape the . character. Now it detects if a path segment needs to be quoted.
• This is a more generic fix compared to the ad-hoc quote_invalid_paths function. A side benefit, it that this PR paves the way for Refactor field iterators to return OwnedTargetPaths #21077.

Testing

Added/enhanced unit tests.

Vector Unit Test

transforms:
  reduce_scalyr:
    type: reduce
    inputs:
    - my_input
    group_by:
    - session
    expire_after_ms: 2000
    max_events: 500
    merge_strategies:
      events: array
tests:
- name: map_reduce_scalyr.no_sev
  inputs:
  - type: vrl
    insert_at: reduce_scalyr
    source: |
      . = {
        "events": {
          "attrs": {
            "msg": "foo"
          },
          "sev": 3,
          "ts": "1602349656452332000"
        },
        "session": "session",
        "sessionInfo": {
          "kubernetes.cluster": "cluster",
          "kubernetes.container-name": "container",
          "kubernetes.namespace.name": "namespace",
          "kubernetes.pod.name": "pod",
          "logfile": "p",
          "serverHost": "n"
        },
        "token": "token"
      }
  - type: vrl
    insert_at: reduce_scalyr
    source: |
      . = {
        "events": {
          "attrs": {
            "msg": "bar"
          },
          "sev": 3,
          "ts": "1602349656460000000"
        },
        "session": "session",
        "sessionInfo": {
          "kubernetes.cluster": "cluster",
          "kubernetes.container-name": "container",
          "kubernetes.namespace.name": "namespace",
          "kubernetes.pod.name": "pod",
          "logfile": "p",
          "serverHost": "n"
        },
        "token": "token"
      }
  outputs:
  - extract_from: reduce_scalyr
    conditions:
    - type: vrl
      source: |
        assert_eq!(., {
          "events": [
            {
              "ts": "1602349656452332000",
              "sev": 3,
              "attrs": {
                "msg": "foo",
              },
            },
            {
              "ts": "1602349656460000000",
              "sev": 3,
              "attrs": {
                "msg": "bar",
              },
            },
          ],
          "session": "session",
          "sessionInfo": {
            "kubernetes.cluster": "cluster",
            "kubernetes.container-name": "container",
            "kubernetes.namespace.name": "namespace",
            "kubernetes.pod.name": "pod",
            "logfile": "p",
            "serverHost": "n"
          },
          "token": "token",
        })

[datadog-vectordotdev]

Datadog Report

Branch report: pront/i21165
Commit report: 1fe6e1b
Test service: vector

✅ 0 Failed, 7 Passed, 0 Skipped, 25.49s Total Time

[jszwedko]

Awesome! This is definitely cleaner 👍 I tested it locally and it seems to work. I appreciate the additional tests here too.

[jszwedko]

🎉

[github-actions]

Regression Detector Results

Run ID: fcdf8565-c858-4041-acfc-860b915dcee6 Metrics dashboard

Baseline: d174d55
Comparison: f2155f1

Performance changes are noted in the perf column of each table:

• ✅ = significantly better comparison variant performance
• ❌ = significantly worse comparison variant performance
• ➖ = no significant change in performance

No significant changes in experiment optimization goals

Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf	experiment	goal	Δ mean %	Δ mean % CI	links
➖	file_to_blackhole	egress throughput	-6.28	[-13.20, +0.64]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	links
➖	syslog_log2metric_tag_cardinality_limit_blackhole	ingress throughput	+1.97	[+1.87, +2.08]
➖	syslog_log2metric_splunk_hec_metrics	ingress throughput	+1.73	[+1.62, +1.85]
➖	datadog_agent_remap_datadog_logs_acks	ingress throughput	+1.07	[+0.94, +1.20]
➖	syslog_loki	ingress throughput	+0.63	[+0.56, +0.70]
➖	syslog_splunk_hec_logs	ingress throughput	+0.53	[+0.44, +0.62]
➖	http_text_to_http_json	ingress throughput	+0.49	[+0.36, +0.62]
➖	http_to_http_noack	ingress throughput	+0.16	[+0.08, +0.24]
➖	http_to_s3	ingress throughput	+0.16	[-0.11, +0.43]
➖	http_elasticsearch	ingress throughput	+0.11	[-0.07, +0.29]
➖	http_to_http_json	ingress throughput	+0.03	[-0.01, +0.06]
➖	splunk_hec_to_splunk_hec_logs_acks	ingress throughput	+0.01	[-0.08, +0.11]
➖	otlp_grpc_to_blackhole	ingress throughput	-0.01	[-0.12, +0.10]
➖	splunk_hec_to_splunk_hec_logs_noack	ingress throughput	-0.01	[-0.11, +0.08]
➖	splunk_hec_indexer_ack_blackhole	ingress throughput	-0.01	[-0.09, +0.06]
➖	splunk_hec_route_s3	ingress throughput	-0.08	[-0.40, +0.24]
➖	datadog_agent_remap_datadog_logs	ingress throughput	-0.11	[-0.28, +0.06]
➖	http_to_http_acks	ingress throughput	-0.23	[-1.50, +1.04]
➖	syslog_regex_logs2metric_ddmetrics	ingress throughput	-0.29	[-0.40, -0.18]
➖	fluent_elasticsearch	ingress throughput	-0.33	[-0.82, +0.16]
➖	datadog_agent_remap_blackhole	ingress throughput	-0.82	[-0.92, -0.71]
➖	syslog_humio_logs	ingress throughput	-1.36	[-1.48, -1.24]
➖	datadog_agent_remap_blackhole_acks	ingress throughput	-2.15	[-2.26, -2.04]
➖	otlp_http_to_blackhole	ingress throughput	-3.05	[-3.18, -2.93]
➖	socket_to_socket_blackhole	ingress throughput	-3.23	[-3.30, -3.16]
➖	syslog_log2metric_humio_metrics	ingress throughput	-4.15	[-4.27, -4.03]
➖	file_to_blackhole	egress throughput	-6.28	[-13.20, +0.64]

Explanation

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI".

For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true:

1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.

2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that if our statistical model is accurate, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants.

3. Its configuration does not mark it "erratic".