{% with messages = get_flashed_messages(with_categories=true) %} {% if messages %} {% for category, message in messages %}
{{ message }}
{% endfor %} {% endif %} {% endwith %}

Table Statistics

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Table Query Analysis

{{ stats|length }} tables analyzed

These statistics show how queries interact with your database tables. Click on "View Details" to see more information about each table.

{% for table in stats %} {% endfor %}
Table Name Total Queries Read Queries Write Queries Total Time (ms) Read Time (ms) Write Time (ms) Actions
{{ table.table_name }} {{ table.total_queries }} {{ table.read_queries }} {{ table.write_queries }} {{ "%.2f"|format(table.total_time) }} {{ "%.2f"|format(table.total_read_time) }} {{ "%.2f"|format(table.total_write_time) }} View Details

Table Insights

Table Usage Patterns
  • Tables with high read counts but low write counts are good candidates for query optimization and indexing
  • Tables with high write counts may benefit from optimizing insert/update operations
  • Tables with high total query time are performance bottlenecks in your database
Data Relationships
  • Use the lineage graph to understand how data flows between tables
  • Identify central tables that many queries depend on
  • Find unused or rarely used tables that might be candidates for archiving