eventhouse-authoring-cli（eventhouse authoring CLI 搜索）

Update Check — ONCE PER SESSION (mandatory) The first time this skill is used in a session, run the check-updates skill before proceeding. - GitHub Copilot CLI / VS Code: invoke the check-updates skill. - Claude Code / Cowork / Cursor / Windsurf / Codex: compare local vs remote package.json version. - Skip if the check was already performed earlier in this session.

CRITICAL NOTES 1. To find the workspace details (including its ID) from workspace name: list all workspaces and, then, use JMESPath filtering 2. To find the item details (including its ID) from workspace ID, item type, and item name: list all items of that type in that workspace and, then, use JMESPath filtering

eventhouse-authoring-cli — Eventhouse Authoring and Management via CLI

Table of Contents

Tool Stack

Connection

Same as eventhouse-consumption-cli. Authoring requires elevated roles:

# Discover KQL Database query URI
WS_ID="<workspace-id>"
az rest --method GET \
  --url "https://api.fabric.microsoft.com/v1/workspaces/${WS_ID}/kqlDatabases" \
  --resource "https://api.fabric.microsoft.com" \
  | jq '.value[] | {name: .displayName, queryUri: .properties.queryServiceUri}'

# Set connection variables
CLUSTER_URI="https://<cluster>.kusto.fabric.microsoft.com"
DB_NAME="MyDatabase"

# Verify admin access
cat > /tmp/kql_body.json << EOF
{"db":"${DB_NAME}","csl":".show database ${DB_NAME} principals | where Role == 'Admin'"}
EOF
az rest --method POST \
  --url "${CLUSTER_URI}/v1/rest/mgmt" \
  --resource "https://kusto.kusto.windows.net" \
  --headers "Content-Type=application/json" \
  --body @/tmp/kql_body.json \
  | jq '.Tables[0].Rows'

Authoring Scope

Execute KQL Command

All KQL management commands in this skill follow the same az rest pattern. After setting CLUSTER_URI and DB, write the JSON body to /tmp/kql_body.json and execute:

cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":"<KQL management command>"}
EOF
az rest --method POST \
  --url "${CLUSTER_URI}/v1/rest/mgmt" \
  --resource "https://kusto.kusto.windows.net" \
  --headers "Content-Type=application/json" \
  --body @/tmp/kql_body.json \
  | jq '.Tables[0].Rows'

Nested JSON — For commands whose KQL contains embedded JSON (policies, mappings), use << 'EOF' (single-quoted) to prevent shell expansion of backslash-escaped quotes, and replace ${DB} with the literal database name.

PowerShell equivalent — @{db=$Database;csl=$Command} | ConvertTo-Json -Compress | Out-File $env:TEMP\kql_body.json -Encoding utf8NoBOM then --body "@$env:TEMP\kql_body.json". See PowerShell Templates.

Table Management via CLI

Create Table (Idempotent)

cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".create-merge table Events (Timestamp: datetime, EventType: string, UserId: string, Properties: dynamic, Duration: real)"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Add Column

cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".alter-merge table Events (Region: string)"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Drop Table

cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".drop table Events ifexists"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Data Ingestion via CLI

Inline Ingestion (Testing)

cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".ingest inline into table Events <| 2025-01-15T10:00:00Z,Login,user1,{},0.5\n2025-01-15T10:01:00Z,Click,user2,{},0.2"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Ingest from Storage

cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".ingest into table Events (h'https://mystorage.blob.core.windows.net/data/events.csv.gz;impersonate') with (format='csv', ingestionMappingReference='EventsCsvMapping', ignoreFirstRecord=true)"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Ingest from OneLake

cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".ingest into table Events (h'abfss://workspace@onelake.dfs.fabric.microsoft.com/lakehouse.Lakehouse/Files/events.parquet;impersonate') with (format='parquet')"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Set-or-Append from Query

cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".set-or-append CleanEvents <| RawEvents | where IsValid == true | project Timestamp, EventType, UserId"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Policies via CLI

Retention

# Set 365-day retention
cat > /tmp/kql_body.json << 'EOF'
{"db":"MyDB","csl":".alter table Events policy retention '{\"SoftDeletePeriod\":\"365.00:00:00\",\"Recoverability\":\"Enabled\"}'"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Caching (Hot Cache)

# Keep last 30 days in hot cache
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".alter table Events policy caching hot = 30d"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Streaming Ingestion

cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".alter table Events policy streamingingestion enable"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Materialized Views via CLI

# Create materialized view with backfill
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".create materialized-view with (backfill=true) HourlyEventCounts on table Events { Events | summarize Count = count(), LastSeen = max(Timestamp) by EventType, bin(Timestamp, 1h) }"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

# Check health
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".show materialized-view HourlyEventCounts statistics"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Functions and Update Policies via CLI

Create Function

cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".create-or-alter function with (docstring='Parse raw events', folder='ETL') ParseRawEvents() { RawEvents | extend Parsed = parse_json(RawData) | project Timestamp = todatetime(Parsed.timestamp), EventType = tostring(Parsed.eventType), UserId = tostring(Parsed.userId) }"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Create Update Policy

cat > /tmp/kql_body.json << 'EOF'
{"db":"MyDB","csl":".alter table ParsedEvents policy update @'[{\"IsEnabled\":true,\"Source\":\"RawEvents\",\"Query\":\"ParseRawEvents()\",\"IsTransactional\":true}]'"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Schema Evolution via CLI

Safe Schema Deployment Script

Save management commands in a .kql file (one per line), then execute each command via az rest:

# deploy_schema.kql contains one command per line:
# .create-merge table Events (Timestamp: datetime, EventType: string, UserId: string, Properties: dynamic)
# .create-merge table ParsedEvents (Timestamp: datetime, EventType: string, UserId: string, PageName: string)
# .alter table Events policy retention '{\"SoftDeletePeriod\":\"365.00:00:00\",\"Recoverability\":\"Enabled\"}'
# .alter table Events policy caching hot = 30d

# Execute each command from the file (see "Execute KQL Command" section)
while IFS= read -r cmd; do
  [[ "$cmd" =~ ^// ]] && continue   # skip comment lines
  [[ -z "$cmd" ]] && continue        # skip blank lines
  cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":"${cmd}"}
EOF
  az rest --method POST \
    --url "${CLUSTER_URI}/v1/rest/mgmt" \
    --resource "https://kusto.kusto.windows.net" \
    --headers "Content-Type=application/json" \
    --body @/tmp/kql_body.json \
    | jq '.Tables[0].Rows'
done < deploy_schema.kql

Export Current Schema

cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".show database ${DB} schema as csl script"}
EOF
az rest --method POST \
  --url "${CLUSTER_URI}/v1/rest/mgmt" \
  --resource "https://kusto.kusto.windows.net" \
  --headers "Content-Type=application/json" \
  --body @/tmp/kql_body.json \
  | jq -r '.Tables[0].Rows[][0]' > current_schema.kql

Monitoring Authoring Operations

// Recent management commands
.show commands
| where StartedOn > ago(1h)
| project StartedOn, CommandType, Text = substring(Text, 0, 100), State, Duration
| order by StartedOn desc

// Ingestion failures
.show ingestion failures
| where FailedOn > ago(24h)
| summarize FailureCount = count() by ErrorCode, Table
| order by FailureCount desc

// Materialized view health
.show materialized-views
| project Name, IsEnabled, IsHealthy, MaterializedTo

Must / Prefer / Avoid / Troubleshooting

Must

• Clarify before acting on ambiguous prompts — if the request does not specify a target table, operation type, or schema (e.g. "set up my Eventhouse", "configure my database"), ask the user what they want to do. Never infer intent and apply management commands autonomously. Irreversible side-effects (policy changes, schema mutations, data ingestion) require explicit user intent.
• Use idempotent commands — .create-merge table, .create-or-alter function, .create table ifnotexists.
• Verify permissions before authoring — must have Admin or Ingestor role.
• Test update policies by running the function independently before attaching.
• Include impersonate in storage URIs when ingesting from OneLake or Blob Storage.

Prefer

• az rest with loop for deploying multi-command schema files.
• Fabric KQL MCP server for agent-integrated ingestion and management workflows.
• .create-merge table over .create table for safe schema evolution.
• Materialized views over repeated expensive aggregation queries.
• Script-based CI/CD — export schema with .show database DB schema as csl script, store in git.

Avoid

• .drop table without ifexists — fails on missing tables.
• .alter table to add columns — use .alter-merge table instead (additive only).
• Ingestion without mappings for CSV/JSON — column order or field names may not match.
• Hardcoded storage URIs — parameterise in scripts.
• Disabling materialized views without understanding the re-backfill cost.

Troubleshooting

Agentic Workflows

Exploration Before Authoring

Always check for explicit intent before doing anything:

Step 0 → Is the request specific? Does it name a table, operation, and/or schema?
         → NO  → Ask: "What would you like to set up? Options: create tables,
                  configure policies, set up ingestion mappings, create materialized views."
                  STOP — do not proceed until user specifies.
         → YES → Continue to Step 1.
Step 1 → .show tables details                        // what exists?
Step 2 → .show table <TABLE> schema as json          // current columns
Step 3 → .show table <TABLE> policy retention        // current policies
Step 4 → Plan changes (create-merge, alter, etc.)
Step 5 → Execute changes
Step 6 → Verify: .show table <TABLE> schema as json  // confirm changes

Script Generation Workflow

Step 1 → Understand requirements from user
Step 2 → Generate KQL management commands
Step 3 → Save to .kql file
Step 4 → Deploy via az rest (one command at a time)
Step 5 → Verify deployed state matches intent

Examples

Example 1: Create Table with Policies and Mapping

# Create table
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".create-merge table SensorData (Timestamp: datetime, DeviceId: string, Temperature: real, Humidity: real, Location: dynamic)"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

# Set retention
cat > /tmp/kql_body.json << 'EOF'
{"db":"MyDB","csl":".alter table SensorData policy retention '{\"SoftDeletePeriod\":\"90.00:00:00\",\"Recoverability\":\"Enabled\"}'"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

# Set caching
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".alter table SensorData policy caching hot = 7d"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

# Create JSON mapping
cat > /tmp/kql_body.json << 'EOF'
{"db":"MyDB","csl":".create table SensorData ingestion json mapping 'SensorJsonMapping' '[{\"column\":\"Timestamp\",\"path\":\"$.ts\",\"datatype\":\"datetime\"},{\"column\":\"DeviceId\",\"path\":\"$.deviceId\",\"datatype\":\"string\"},{\"column\":\"Temperature\",\"path\":\"$.temp\",\"datatype\":\"real\"},{\"column\":\"Humidity\",\"path\":\"$.humidity\",\"datatype\":\"real\"},{\"column\":\"Location\",\"path\":\"$.location\",\"datatype\":\"dynamic\"}]'"}
EOF

Execute /tmp/kql_body.json — see Execute KQL Command

Example 2: ETL with Update Policy

// 1. Target table
.create-merge table ParsedLogs (Timestamp: datetime, Level: string, Message: string, Source: string)

// 2. Transform function
.create-or-alter function ParseRawLogs() {
    RawLogs
    | extend J = parse_json(RawMessage)
    | project
        Timestamp = todatetime(J.timestamp),
        Level = tostring(J.level),
        Message = tostring(J.message),
        Source = tostring(J.source)
}

// 3. Attach update policy
.alter table ParsedLogs policy update
@'[{"IsEnabled":true,"Source":"RawLogs","Query":"ParseRawLogs()","IsTransactional":true}]'

Agent Integration Notes

• This skill covers authoring operations — creating/altering database objects and ingesting data.
• For read-only queries and data exploration, delegate to eventhouse-consumption-cli.
• For cross-workload orchestration, delegate to the FabricDataEngineer agent.
• All management commands require elevated database roles (Admin or Ingestor).