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Introduction

Query reference overview

APL

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Functions
Scalar functions
Array functions
Overview
array_concat
array_extract
array_iff
array_index_of
array_length
array_reverse
array_rotate_left
array_rotate_right
array_select_dict
array_shift_left
array_shift_right
array_slice
array_sort_asc
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array_sum
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isarray
len
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case
iff
Conversion functions
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dynamic_to_json
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toarray
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Datetime functions
Overview
ago
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getmonth
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startofday
startofmonth
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startofyear
unixtime_microseconds_todatetime
unixtime_milliseconds_todatetime
unixtime_nanoseconds_todatetime
unixtime_seconds_todatetime
week_of_year
GenAI functions
Overview
genai_concat_contents
genai_conversation_turns
genai_cost
genai_estimate_tokens
genai_extract_assistant_response
genai_extract_function_results
genai_extract_system_prompt
genai_extract_tool_calls
genai_extract_user_prompt
genai_get_content_by_index
genai_get_content_by_role
genai_get_pricing
genai_get_role
genai_has_tool_calls
genai_input_cost
genai_is_truncated
genai_message_roles
genai_output_cost
Hash functions
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hash
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IP functions
Overview
format_ipv4
format_ipv4_mask
geo_info_from_ip_address
has_any_ipv4
has_any_ipv4_prefix
has_ipv4
has_ipv4_prefix
ipv4_compare
ipv4_is_in_range
ipv4_is_in_any_range
ipv4_is_match
ipv4_is_private
ipv4_netmask_suffix
ipv6_compare
ipv6_is_in_any_range
ipv6_is_in_range
ipv6_is_match
parse_ipv4
parse_ipv4_mask
Mathematical functions
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abs
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atan2
cos
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degrees
exp
exp2
exp10
gamma
isfinite
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isint
isnan
log
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loggamma
max_of
min_of
not
pi
pow
radians
rand
range
round
set_difference
set_has_element
set_intersect
set_union
sign
sin
sqrt
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Metadata functions
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column_ifexists
cursor_current
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Pair functions
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find_pair
pair
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Rounding functions
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bin
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floor
String functions
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base64_decode_toarray
base64_decode_tostring
base64_encode_fromarray
base64_encode_tostring
coalesce
countof
countof_regex
extract
extract_all
format_bytes
format_url
gettype
indexof
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isascii
isempty
isnotempty
isnotnull
isnull
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parse_csv
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quote
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replace_regex
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unicode_codepoints_to_string
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SQL functions
Overview
parse_sql
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Time series functions
Overview
series_abs
series_acos
series_add
series_asin
series_atan
series_ceiling
series_cos
series_cosine_similarity
series_divide
series_dot_product
series_equals
series_exp
series_fft
series_fill_backward
series_fill_const
series_fill_forward
series_fill_linear
series_fir
series_floor
series_greater
series_greater_equals
series_ifft
series_iir
series_less
series_less_equals
series_log
series_magnitude
series_max
series_min
series_multiply
series_not_equals
series_pearson_correlation
series_pow
series_sign
series_sin
series_stats
series_stats_dynamic
series_subtract
series_sum
series_tan
Type functions
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isimei
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isstring
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Aggregation functions
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avg
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count
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dcount
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histogram
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make_list
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max
maxif
min
minif
percentile
percentileif
percentiles_array
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spotlight
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topk
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in
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Reference
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Migrate
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MPL

Language featuresSample queriesMigrate
APL/Functions

series_equals

This page explains how to use the series_equals function in APL.

The series_equals function compares each element in a numeric dynamic array (series) to a specified value and returns a boolean array indicating which elements are equal to that value. This function is useful for filtering, conditional analysis, and identifying specific values within time series data.

You can use series_equals when you want to identify occurrences of specific values in your data, such as finding exact matches for thresholds, status codes, or target values. Typical applications include anomaly detection, data validation, and conditional processing of time series data.

Usage

Syntax

APL
series_equals(array, value)

Parameters

ParameterTypeDescription
arraydynamicA dynamic array of real numeric values.
valuenumericThe value to compare against each array element.

Returns

A dynamic array of boolean values where each element indicates whether the corresponding input element equals the specified value.

Use case examples

In log analysis, you can use series_equals to identify requests that match specific duration thresholds or status codes across multiple requests per user.

Query

APLRun in Playground
['sample-http-logs']
| summarize durations = make_list(req_duration_ms) by id
| extend is_200ms = series_equals(durations, 200)

Output

iddurationsis_200ms
u123[150, 200, 250][false, true, false]
u456[200, 200, 180][true, true, false]

This query identifies which request durations exactly equal 200ms for each user, useful for finding requests that hit specific performance targets.

In OpenTelemetry traces, you can use series_equals to identify spans with specific duration values or status codes across multiple spans per service.

Query

APLRun in Playground
['otel-demo-traces']
| summarize durations = make_list(toreal(duration)) by ['service.name']
| extend is_1s = series_equals(durations, toreal(1s))

Output

service.namedurationsis_1s
frontend[800, 1000, 1200][false, true, false]
productcatalogservice[1000, 1000, 900][true, true, false]

This query identifies spans with exactly 1-second durations per service, useful for finding spans that hit specific latency targets.

In security logs, you can use series_equals to identify requests with specific status codes or durations that might indicate security events.

Query

APLRun in Playground
['sample-http-logs']
| summarize durations = make_list(req_duration_ms) by status
| extend is_500ms = series_equals(durations, 500)

Output

statusdurationsis_500ms
200[300, 500, 400][false, true, false]
500[500, 500, 600][true, true, false]

This query identifies requests with exactly 500ms duration grouped by status code, useful for finding requests that hit specific timing thresholds.

List of related functions

  • series_greater: Returns elements greater than a specified value. Use when you need threshold-based filtering instead of exact matches.
  • series_greater_equals: Returns elements greater than or equal to a specified value. Use for inclusive threshold comparisons.
  • series_less: Returns elements less than a specified value. Use for lower-bound filtering.
  • series_less_equals: Returns elements less than or equal to a specified value. Use for inclusive lower-bound comparisons.
  • series_not_equals: Returns elements not equal to a specified value. Use for exclusion-based filtering.

Other query languages

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