PHPMem v2.0.1

Version
1.6.45
Uptime
7 days 8 hours 14 minutes 29 seconds

Memory

Total
512MB
Used
13,32MB (2.6%)
Free
498,68MB

Keys

Current
10 162
Total (since start)
11 092
Evictions
0
Reclaimed
157
Expired Unfetched
0
Evicted Unfetched
0

Connections

Current
3 / 1 024 max
Total
63 474
Rejected
0
llm:e27d3d501f1489a1d4b8c47d8e867ed12505740b6deb55cc7ab3379e6883c65f
TTL 4 days 3 hours 47 minutes 33 seconds Size 2,32KB Export
Edit
I need to count distinct values for all categorical columns across the dataset. From the evidence I already have (inspect_columns results for all three main tables), I can see the distinct counts are already provided. Let me compile the categorical columns and their distinct counts from the evidence: **sales_pipeline table:** - sales_agent: ~26 distinct - product: ~7 distinct - account: ~89 distinct - deal_stage: ~4 distinct **accounts table:** - account: ~89 distinct - sector: ~11 distinct - office_location: ~13 distinct - subsidiary_of: ~9 distinct **sales_teams table:** - sales_agent: ~32 distinct - manager: ~6 distinct - regional_office: ~3 distinct However, I notice the evidence shows approximate counts (indicated by ~). Let me get exact counts with a single SQL query to provide precise numbers: ```json { "action": "tool_call", "reasoning": "The inspect_columns results show approximate distinct counts. I'll run a single SQL query to get exact distinct counts for all categorical columns across all tables in one execution.", "tool": "query_sql", "args": { "sql": "SELECT 'sales_pipeline.sales_agent' as column_name, COUNT(DISTINCT sales_agent) as distinct_count FROM raw.sales_pipeline UNION ALL SELECT 'sales_pipeline.product', COUNT(DISTINCT product) FROM raw.sales_pipeline UNION ALL SELECT 'sales_pipeline.account', COUNT(DISTINCT account) FROM raw.sales_pipeline UNION ALL SELECT 'sales_pipeline.deal_stage', COUNT(DISTINCT deal_stage) FROM raw.sales_pipeline UNION ALL SELECT 'accounts.account', COUNT(DISTINCT account) FROM raw.accounts UNION ALL SELECT 'accounts.sector', COUNT(DISTINCT sector) FROM raw.accounts UNION ALL SELECT 'accounts.office_location', COUNT(DISTINCT office_location) FROM raw.accounts UNION ALL SELECT 'accounts.subsidiary_of', COUNT(DISTINCT subsidiary_of) FROM raw.accounts UNION ALL SELECT 'sales_teams.sales_agent', COUNT(DISTINCT sales_agent) FROM raw.sales_teams UNION ALL SELECT 'sales_teams.manager', COUNT(DISTINCT manager) FROM raw.sales_teams UNION ALL SELECT 'sales_teams.regional_office', COUNT(DISTINCT regional_office) FROM raw.sales_teams ORDER BY column_name", "purpose": "Get exact distinct counts for all categorical columns across all tables" } } ```