PHPMem v2.0.1

Version
1.6.45
Uptime
7 days 15 hours 45 minutes 2 seconds

Memory

Total
512MB
Used
10,72MB (2.09%)
Free
501,28MB

Keys

Current
8 118
Total (since start)
11 096
Evictions
0
Reclaimed
206
Expired Unfetched
0
Evicted Unfetched
0

Connections

Current
3 / 1 024 max
Total
70 546
Rejected
0
llm:85c51e50eab2d78f69772a71c8619a48184ed33054d793844a751311ac1999fb
TTL 3 days 3 hours 29 minutes 25 seconds Size 1,24KB Export
Edit
I need to check for duplicate and near-duplicate rows in the dataset. Let me start by examining the structure and then look for exact duplicates and potential near-duplicates. ```json { "action": "tool_call", "reasoning": "First, I'll check for exact duplicate rows by grouping on all columns except the metadata columns (_ingestion_timestamp, _batch_id, _source_file, _source_system) which are ingestion artifacts. I'll also check if Player ID serves as a unique identifier.", "tool": "query_sql", "args": { "sql": "WITH duplicates AS (SELECT \"Player ID\", Name, Assoc, Gender, \"Birth year\", Activity, \"Playing hand\", \"Playing style\", Grip, COUNT(*) as duplicate_count FROM raw.ittf_player_info GROUP BY \"Player ID\", Name, Assoc, Gender, \"Birth year\", Activity, \"Playing hand\", \"Playing style\", Grip HAVING COUNT(*) > 1) SELECT duplicate_count, COUNT(*) as num_groups, SUM(duplicate_count) as total_rows FROM duplicates GROUP BY duplicate_count ORDER BY duplicate_count DESC", "purpose": "Check for exact duplicate rows based on all business columns (excluding ingestion metadata)", "source": "raw" } } ```