spl-to-apl

安装量: 112
排名: #7651

安装

npx skills add https://github.com/axiomhq/skills --skill spl-to-apl

Type safety: Fields like status are often stored as strings. Always cast before numeric comparison: toint(status) >= 500, not status >= 500.

Critical Differences

  • Time is explicit in APL: SPL time pickers don't translate — add where _time between (ago(1h) .. now())

  • Structure: SPL index=... | command → APL ['dataset'] | operator

  • Join is preview: limited to 50k rows, inner/innerunique/leftouter only

  • cidrmatch args reversed: SPL cidrmatch(cidr, ip) → APL ipv4_is_in_range(ip, cidr)

Core Command Mappings

| search index=... | ['dataset'] | Dataset replaces index

| search field=value | where field == "value" | Explicit where

| where | where | Same

| stats | summarize | Different aggregation syntax

| eval | extend | Create/modify fields

| table / fields | project | Select columns

| fields - | project-away | Remove columns

| rename x as y | project-rename y = x | Rename

| sort / sort - | order by ... asc/desc | Sort

| head N | take N | Limit rows

| top N field | summarize count() by field | top N by count_ | Two-step

| dedup field | summarize arg_max(_time, *) by field | Keep latest

| rex | parse or extract() | Regex extraction

| join | join | Preview feature

| append | union | Combine datasets

| mvexpand | mv-expand | Expand arrays

| timechart span=X | summarize ... by bin(_time, X) | Manual binning

| rare N field | summarize count() by field | order by count_ asc | take N | Bottom N

| spath | parse_json() or json['path'] | JSON access

| transaction | No direct equivalent | Use summarize + make_list

Complete mappings: reference/command-mapping.md

Stats → Summarize

# SPL
| stats count by status

# APL  
| summarize count() by status

Key function mappings

| count | count()

| count(field) | countif(isnotnull(field))

| dc(field) | dcount(field)

| avg/sum/min/max | Same

| median(field) | percentile(field, 50)

| perc95(field) | percentile(field, 95)

| first/last | arg_min/arg_max(_time, field)

| list(field) | make_list(field)

| values(field) | make_set(field)

Conditional count pattern

# SPL
| stats count(eval(status>=500)) as errors by host

# APL
| summarize errors = countif(status >= 500) by host

Complete function list: reference/function-mapping.md

Eval → Extend

# SPL
| eval new_field = old_field * 2

# APL
| extend new_field = old_field * 2

Key function mappings

| if(c, t, f) | iff(c, t, f) | Double 'f'

| case(c1,v1,...) | case(c1,v1,...,default) | Requires default

| len(str) | strlen(str) |

| lower/upper | tolower/toupper |

| substr | substring | 0-indexed in APL

| replace | replace_string |

| tonumber | toint/tolong/toreal | Explicit types

| match(s,r) | s matches regex "r" | Operator

| split(s, d) | split(s, d) | Same

| mvjoin(mv, d) | strcat_array(arr, d) | Join array

| mvcount(mv) | array_length(arr) | Array length

Case statement pattern

# SPL
| eval level = case(
    status >= 500, "error",
    status >= 400, "warning",
    1==1, "ok"
  )

# APL  
| extend level = case(
    status >= 500, "error",
    status >= 400, "warning",
    "ok"
  )

Note: SPL's 1==1 catch-all becomes implicit default in APL.

Rex → Parse/Extract

# SPL
| rex field=message "user=(?<username>\w+)"

# APL - parse with regex
| parse kind=regex message with @"user=(?P<username>\w+)"

# APL - extract function  
| extend username = extract("user=(\\w+)", 1, message)

Simple pattern (non-regex)

# SPL
| rex field=uri "^/api/(?<version>v\d+)/(?<endpoint>\w+)"

# APL
| parse uri with "/api/" version "/" endpoint

Time Handling

SPL time pickers don't translate. Always add explicit time range:

# SPL (time picker: Last 24 hours)
index=logs

# APL
['logs'] | where _time between (ago(24h) .. now())

Timechart translation

# SPL
| timechart span=5m count by status

# APL
| summarize count() by bin(_time, 5m), status

Common Patterns

Error rate calculation

# SPL
| stats count(eval(status>=500)) as errors, count as total by host
| eval error_rate = errors/total*100

# APL
| summarize errors = countif(status >= 500), total = count() by host
| extend error_rate = toreal(errors) / total * 100

Subquery (subsearch)

# SPL
index=logs [search index=errors | fields user_id | format]

# APL
let error_users = ['errors'] | where _time between (ago(1h) .. now()) | distinct user_id;
['logs']
| where _time between (ago(1h) .. now())
| where user_id in (error_users)

Join datasets

# SPL
| join user_id [search index=users | fields user_id, name]

# APL
| join kind=inner (['users'] | project user_id, name) on user_id

Transaction-like grouping

# SPL
| transaction session_id maxspan=30m

# APL (no direct equivalent — reconstruct with summarize)
| summarize 
    start_time = min(_time),
    end_time = max(_time),
    events = make_list(pack("time", _time, "action", action)),
    duration = max(_time) - min(_time)
  by session_id
| where duration <= 30m

String Matching Performance

| field="value" | field == "value" | Fastest

| field="*value*" | field contains "value" | Moderate

| field="value*" | field startswith "value" | Fast

| match(field, regex) | field matches regex "..." | Slowest

Prefer has over contains (word-boundary matching is faster). Use _cs variants for case-sensitive (faster).

Reference

  • reference/command-mapping.md — complete command list

  • reference/function-mapping.md — complete function list

  • reference/examples.md — full query translation examples

  • APL docs: https://axiom.co/docs/apl/introduction

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