/kql

Error Recovery Reference

Complete mapping of common KQL error patterns. For each error: the exact message, a real query that triggered it, and the fix.

Table of Contents

1. E_LOW_MEMORY_CONDITION
2. Join Errors
3. Network / Transient
4. Dynamic Type Errors
5. Unresolved Names
6. Syntax Errors
7. String Comparison
8. extract_all Regex Groups
9. Serialization Required
10. Missing Plugins
11. graph-match Syntax
12. E_RUNAWAY_QUERY

1. E_LOW_MEMORY_CONDITION

Error message: Query execution lacks memory resources to complete (80DA0007): Partial query failure: Low memory condition (E_LOW_MEMORY_CONDITION)

Pattern A: Unfiltered aggregation on large table

// ❌ TRIGGERED ERROR — large table, no pre-filter, too many group-by columns
StormEvents
| summarize dcount(EventType), count() by StartTime, State, Source
| where dcount_EventType > 1

// ✅ FIX — filter first, reduce grouping columns
StormEvents
| where StartTime between (datetime(2007-04-15) .. datetime(2007-04-16))
| summarize dcount(EventType) by State, Source
| where dcount_EventType > 1

Pattern B: Join explosion

// ❌ TRIGGERED ERROR — unconstrained join between two large tables
StormEvents
| join kind=inner (PopulationData) on State

// ✅ FIX — pre-filter both sides, check cardinality first
let filtered_storms = StormEvents | where State == "TEXAS" | summarize by State;
let target_states = PopulationData | project State;
filtered_storms | join kind=inner (target_states) on State

Pattern C: High-cardinality dcount()

// ❌ TRIGGERED ERROR — Full distinct value enumeration on many columns
StormEvents | summarize dcount(EventType), dcount(Source), dcount(BeginLocation) by bin(StartTime, 1h)

// ✅ FIX — filter first, reduce to one dcount
StormEvents
| where StartTime between (datetime(2007-06-01) .. datetime(2007-06-30T23:59:59))
| summarize dcount(EventType) by bin(StartTime, 1h)

Recovery strategy: When you see this error, your query is touching too much data. Options:

1. Add | where time-range or partition filter
2. Reduce by columns in summarize
3. Break the query into smaller time windows
4. Use | sample 10000 for exploration

2. Join Errors

2a. Left/right attribute mismatch

Error message: join: for each left attribute, right attribute should be selected.

// ❌ TRIGGERED ERROR — incomplete on clause
StormEvents | join kind=inner PopulationData on $left.State

// ✅ FIX — specify both sides
StormEvents | join kind=inner (PopulationData) on $left.State == $right.State

// ❌ TRIGGERED ERROR — expression in join condition
StormEvents | join kind=inner (PopulationData) on $left.State == $right.tolower(State)

// ✅ FIX — pre-compute the expression, join on the computed column
StormEvents
| join kind=inner (PopulationData | extend StateLower = tolower(State)) on $left.State == $right.StateLower

2b. Equality only

Error message: join: Only equality is allowed in this context.

// ❌ TRIGGERED ERROR — geo-distance in join predicate
StormEvents | join (nyc_taxi) on geo_distance_2points(BeginLon, BeginLat, pickup_longitude, pickup_latitude) < 1000

// ✅ FIX — pre-bucket into spatial cells
StormEvents
| extend cell = geo_point_to_s2cell(BeginLon, BeginLat, 8)
| join kind=inner (nyc_taxi | extend cell = geo_point_to_s2cell(pickup_longitude, pickup_latitude, 8)) on cell
| where geo_distance_2points(BeginLat, BeginLon, pickup_latitude, pickup_longitude) < 1000

// ❌ TRIGGERED ERROR — range join
StormEvents | join (PopulationData) on $left.DamageProperty > $right.Population

// ✅ FIX — bin values and join on bins
StormEvents
| extend damage_bin = bin(DamageProperty, 1000000)
| join kind=inner (PopulationData | extend damage_bin = bin(Population, 1000000)) on damage_bin
| where DamageProperty > Population

3. Network / Transient

Error message: Failed to process network request for the endpoint: https://kvc4bf3...

Cause: Corrupted cluster URIs or genuine network timeouts.

Recovery strategy:

1. Verify the cluster URI is clean ASCII (no Unicode characters)
2. Retry with a fresh URI from the environment variable
3. If persistent, wait 30 seconds and retry (cluster may be overloaded)

4. Dynamic Type Errors

4a. Summarize by dynamic

Error message: Summarize group key 'Area' is of a 'dynamic' type. Please use an explicit cast

// ❌
| summarize count() by Area
// ✅
| summarize count() by tostring(Area)

4b. Order by dynamic

Error message: order operator: key can't be of dynamic type

// ❌
| order by Properties.Score desc
// ✅
| order by todouble(Properties.Score) desc

4c. Join on dynamic

Error message: join key 'Area' is of a 'dynamic' type. Please use an explicit cast

// ❌
| join kind=inner other on Area
// ✅
| extend Area_str = tostring(Area)
| join kind=inner (other | extend Area_str = tostring(Area)) on Area_str

5. Unresolved Names

Error message: Failed to resolve column or scalar expression named 'X' or Failed to resolve entity 'X'

Common causes

Recovery strategy:

1. Run .show table T schema to check exact column names
2. Check exact table and column names — KQL is case-sensitive for column names
3. If querying a table that should exist but doesn't, check which database you're connected to
4. Most unresolved names are matchable against the cached schema — look for similar names

6. Syntax Errors

6a. Management command in query pipe

Error message: Unexpected control command

This error occurs when a query pipes INTO a management command (not the other way around — management commands CAN have query operators piped after them).

// ✅ WORKS — management output is tabular, can be filtered
.show tables | project TableName | where TableName has "Events"

// ❌ ERROR — query piped into management command
StormEvents | take 5 | .show tables

6b. Reserved words as identifiers

Error message: The name 'shards' needs to be bracketed as ['shards']

// ❌
let shards = ...

// ✅
let ['shards'] = ...
// Or better: rename the variable
let shard_info = ...

6c. Syntax: Expected comma

Various syntax issues, usually from mixing SQL syntax into KQL:

// ❌ SQL-style
SELECT * FROM Table WHERE x = 1

// ✅ KQL-style
Table | where x == 1

7. String Comparison

Error message: Cannot compare values of types string and string. Try adding explicit casts

Despite both sides being strings, KQL sometimes requires explicit casts for computed values.

// ❌ — S2 cell comparison
StormEvents
| extend startCell = geo_point_to_s2cell(BeginLon, BeginLat, 16)
| join kind=inner (nyc_taxi | extend startCell = geo_point_to_s2cell(pickup_longitude, pickup_latitude, 16)) on startCell

// ✅ — explicit tostring()
StormEvents
| extend startCell = tostring(geo_point_to_s2cell(BeginLon, BeginLat, 16))
| join kind=inner (nyc_taxi | extend startCell = tostring(geo_point_to_s2cell(pickup_longitude, pickup_latitude, 16))) on startCell

This occurs most often with geo_point_to_s2cell(), hash(), and strcat() return values.

8. extract_all Regex Groups

Error message: extractall(): argument 2 must be a valid regex with [1..16] matching groups

// ❌ — Missing capturing group
StormEvents | extend words = extract_all(@"[a-zA-Z]{3,}", tolower(EventNarrative))

// ✅ — Add parentheses
StormEvents | extend words = extract_all(@"([a-zA-Z]{3,})", tolower(EventNarrative))

Unlike Python's re.findall(), KQL's extract_all requires at least one () group.

9. Serialization Required

Error message: Function 'row_cumsum' cannot be invoked. The row set must be serialized.

// ❌
StormEvents
| where State == "TEXAS"
| summarize DailyCount = count() by bin(StartTime, 1d)
| extend CumulativeCount = row_cumsum(DailyCount)

// ✅ — add order by (implicitly serializes)
StormEvents
| where State == "TEXAS"
| summarize DailyCount = count() by bin(StartTime, 1d)
| order by StartTime asc
| extend CumulativeCount = row_cumsum(DailyCount)

Affected functions: row_number(), row_cumsum(), prev(), next(), row_window_session().

10. Missing Plugins

Error message: plugin 'geo_point_in_polygon': plugin doesn't exist.

Some KQL functions are plugins that may not be enabled on free-tier clusters.

Recovery strategy: Use the equivalent non-plugin function or fall back to Python for that specific operation.

11. graph-match Syntax

Error message: graph-match operator: variable edge 'path' edges don't have property 'IsVulnerable'

// ❌ — property access on variable-length edge
graph-match (src)-[path*1..3]->(dst)
  where path.IsVulnerable == true

// ✅ — filter edges before building the graph
let edges = Edges | where IsVulnerable == true;
edges
| make-graph SourceId --> TargetId with Nodes on NodeId
| graph-match (src)-[path*1..3]->(dst)
  project src.Name, dst.Name

// ✅ — or use label-based filtering on persistent graphs
graph("MyGraph")
| graph-match (src)-[path*1..3]->(dst)
  where all(path, labels() has "Vulnerable")
  project src.Name, dst.Name

The fix is to pre-filter edges before graph construction.

12. E_RUNAWAY_QUERY

Error message: Runaway query (E_RUNAWAY_QUERY): Join output block exceeded memory budget

// ❌ — unconstrained cross-join on large tables
StormEvents | join kind=inner (nyc_taxi) on $left.EventId == $right.passenger_count

// ✅ — check cardinality first, pre-filter aggressively
// Step 1: StormEvents | summarize dcount(State)  → 67 — OK
// Step 2: PopulationData | count  → check if manageable
// Step 3: Pre-filter, then join
StormEvents
| where State in ("NEW YORK", "TEXAS")
| join kind=inner (PopulationData) on State
| take 5 | project State, EventType, Population

Prevention: Always dcount() both join sides before executing. If left × right > 1M, add filters.