CHART_CONFIGS = {
# ===== ALL USERS AGGREGATE ANALYSIS =====
"user_unoptimized_query": [
{
"chart_type": "bar",
"x_axis": "USER_NAME",
"y_axis": "WEIGHTED_SCORE",
"title": "Top 20 Inefficient Users by Weighted Score",
"color_field": "COST_STATUS",
"colors": {
"High Cost": "rgba(255, 99, 132, 0.6)",
"Normal": "rgba(54, 162, 235, 0.6)",
},
"tooltip_fields": [
"TOTAL_QUERIES",
"TOTAL_CREDITS",
"FAILURE_CANCELLATION_RATE_PCT",
"RECOMMENDATIONS",
],
},
{
"chart_type": "stacked_bar",
"x_axis": "USER_NAME",
"y_axis": [
"SPILLED_QUERIES",
"PEAK_HOUR_LONG_RUNNING_QUERIES",
"SELECT_STAR_QUERIES",
"UNPARTITIONED_SCAN_QUERIES",
"COMPLEX_JOIN_QUERIES",
"HIGH_COMPILE_QUERIES",
],
"stack_field": "Inefficiency Type",
"title": "Cost-Related Inefficiency Breakdown by User",
"colors": {
"SPILLED_QUERIES": "rgba(255, 99, 132, 0.6)",
"PEAK_HOUR_LONG_RUNNING_QUERIES": "rgba(255, 206, 86, 0.6)",
"SELECT_STAR_QUERIES": "rgba(75, 192, 192, 0.6)",
"UNPARTITIONED_SCAN_QUERIES": "rgba(153, 102, 255, 0.6)",
"COMPLEX_JOIN_QUERIES": "rgba(199, 199, 199, 0.6)",
"HIGH_COMPILE_QUERIES": "rgba(255, 99, 71, 0.6)",
},
"tooltip_fields": ["RECOMMENDATIONS", "TOTAL_CREDITS"],
},
{
"chart_type": "grouped_bar",
"x_axis": "USER_NAME",
"y_axis": [
"SPILLED_QUERIES",
"PEAK_HOUR_LONG_RUNNING_QUERIES",
"SELECT_STAR_QUERIES",
"UNPARTITIONED_SCAN_QUERIES",
"COMPLEX_JOIN_QUERIES",
"HIGH_COMPILE_QUERIES",
],
"stack_field": "Inefficiency Type",
"title": "Cost-Related Inefficiency Comparison by User",
"colors": {
"SPILLED_QUERIES": "rgba(255, 99, 132, 0.6)",
"PEAK_HOUR_LONG_RUNNING_QUERIES": "rgba(255, 206, 86, 0.6)",
"SELECT_STAR_QUERIES": "rgba(75, 192, 192, 0.6)",
"UNPARTITIONED_SCAN_QUERIES": "rgba(153, 102, 255, 0.6)",
"COMPLEX_JOIN_QUERIES": "rgba(199, 199, 199, 0.6)",
"HIGH_COMPILE_QUERIES": "rgba(255, 99, 71, 0.6)",
},
"tooltip_fields": ["RECOMMENDATIONS", "TOTAL_CREDITS"],
},
{
"chart_type": "pie",
"y_axis": [
"OVER_PROVISIONED_QUERIES",
"SELECT_STAR_QUERIES",
"ZERO_RESULT_QUERIES",
"UNTAGGED_QUERIES",
],
"stack_field": "Inefficiency Type",
"title": "Performance-Related Distribution of Inefficiency Types",
"colors": [
"rgba(54, 162, 235, 0.6)",
"rgba(75, 192, 192, 0.6)",
"rgba(83, 102, 255, 0.6)",
"rgba(144, 238, 144, 0.6)",
],
"tooltip_fields": ["USER_NAME", "TOTAL_CREDITS", "RECOMMENDATIONS"],
},
# Additional charts for all users analysis
{
"chart_type": "horizontal_bar",
"x_axis": "TOTAL_CREDITS",
"y_axis": "USER_NAME",
"title": "Top Users by Total Credit Consumption",
"color_field": "COST_STATUS",
"colors": {
"High Cost": "rgba(255, 99, 132, 0.6)",
"Normal": "rgba(54, 162, 235, 0.6)",
},
"tooltip_fields": ["WEIGHTED_SCORE", "TOTAL_QUERIES", "RECOMMENDATIONS"],
},
{
"chart_type": "donut",
"y_axis": [
"SPILLED_QUERIES",
"OVER_PROVISIONED_QUERIES",
"PEAK_HOUR_LONG_RUNNING_QUERIES",
"SELECT_STAR_QUERIES",
"UNPARTITIONED_SCAN_QUERIES",
"REPEATED_QUERIES",
"COMPLEX_JOIN_QUERIES",
"ZERO_RESULT_QUERIES",
"HIGH_COMPILE_QUERIES",
"UNTAGGED_QUERIES",
],
"title": "Overall Inefficiency Pattern Distribution",
"colors": [
"rgba(255, 99, 132, 0.6)",
"rgba(54, 162, 235, 0.6)",
"rgba(255, 206, 86, 0.6)",
"rgba(75, 192, 192, 0.6)",
"rgba(153, 102, 255, 0.6)",
"rgba(255, 159, 64, 0.6)",
"rgba(199, 199, 199, 0.6)",
"rgba(83, 102, 255, 0.6)",
"rgba(255, 99, 71, 0.6)",
"rgba(144, 238, 144, 0.6)",
],
"tooltip_fields": ["TOTAL_CREDITS"],
}
],
# Additional aggregate charts for other queries
"bad_practice_impact_all": [
{
"chart_type": "bar",
"x_axis": "USER_NAME",
"y_axis": "TOTAL_COST_IMPACT",
"color_field": "ISSUE_DESCRIPTION",
"title": "Cost Impact of Bad Practices by User",
"colors": {
"Frequent SELECT * usage detected.": "rgba(255, 99, 132, 0.6)",
"High unpartitioned scan frequency.": "rgba(54, 162, 235, 0.6)",
"Repeated queries not leveraging caching.": "rgba(255, 206, 86, 0.6)",
"Excessive complex query patterns.": "rgba(75, 192, 192, 0.6)",
"Mixed bad practices.": "rgba(153, 102, 255, 0.6)",
},
"tooltip_fields": ["RECOMMENDATION", "TOTAL_QUERIES"],
},
{
"chart_type": "stacked_bar",
"x_axis": "USER_NAME",
"y_axis": ["SELECT_STAR_QUERIES", "UNPARTITIONED_SCAN_QUERIES", "REPEATED_QUERIES", "COMPLEX_JOIN_QUERIES"],
"title": "Bad Practice Query Count Breakdown by User",
"colors": {
"SELECT_STAR_QUERIES": "rgba(255, 99, 132, 0.6)",
"UNPARTITIONED_SCAN_QUERIES": "rgba(54, 162, 235, 0.6)",
"REPEATED_QUERIES": "rgba(255, 206, 86, 0.6)",
"COMPLEX_JOIN_QUERIES": "rgba(75, 192, 192, 0.6)",
},
"tooltip_fields": ["TOTAL_COST_IMPACT", "RECOMMENDATION"],
}
],
"user_value_vs_cost_quadrant": [
{
"chart_type": "bar",
"x_axis": "USER_NAME",
"y_axis": "COST_IMPACT",
"color_field": "USER_SEGMENT",
"title": "Cost Impact by User Optimization Segment",
"colors": {
"High Efficiency - High Cost": "rgba(75, 192, 192, 0.6)",
"Low Efficiency - High Cost (OPTIMIZE)": "rgba(255, 99, 132, 0.6)",
"High Efficiency - Low Cost (IDEAL)": "rgba(54, 162, 235, 0.6)",
"Low Efficiency - Low Cost (MONITOR)": "rgba(255, 206, 86, 0.6)",
},
"tooltip_fields": ["EFFICIENCY_SCORE", "QUERY_COUNT"],
}
],
"user_efficiency_matrix": [
{
"chart_type": "bar",
"x_axis": "USER_NAME",
"y_axis": "TOTAL_COST",
"color_field": "RISK_LEVEL",
"title": "User Risk Assessment by Total Cost",
"colors": {
"HIGH_RISK": "rgba(255, 99, 132, 0.6)",
"MEDIUM_RISK": "rgba(255, 206, 86, 0.6)",
"OPTIMIZED": "rgba(54, 162, 235, 0.6)",
},
"tooltip_fields": [
"RECOMMENDATION",
"COST_EFFICIENCY_SCORE",
"PERFORMANCE_EFFICIENCY_SCORE",
],
}
],
# ===== SINGLE USER ANALYSIS =====
"single_user_analysis": [
# User Overview Card (showing key metrics)
{
"chart_type": "metric_card",
"title": "User Performance Overview",
"metrics": [
{"field": "WEIGHTED_SCORE", "label": "Inefficiency Score", "format": "number"},
{"field": "COST_STATUS", "label": "Cost Status", "format": "text"},
{"field": "TOTAL_QUERIES", "label": "Total Queries", "format": "number"},
{"field": "TOTAL_CREDITS", "label": "Total Credits", "format": "currency"},
],
"recommendations_field": "RECOMMENDATIONS"
},
# Cost-Related Issues Breakdown
{
"chart_type": "grouped_bar",
"x_axis": "METRIC_TYPE",
"y_axis": [
"SPILLED_QUERIES",
"PEAK_HOUR_LONG_RUNNING_QUERIES",
"HIGH_COMPILE_QUERIES",
"OVER_PROVISIONED_QUERIES"
],
"title": "Cost-Related Inefficiency Analysis",
"colors": {
"SPILLED_QUERIES": "rgba(255, 99, 132, 0.6)",
"PEAK_HOUR_LONG_RUNNING_QUERIES": "rgba(255, 206, 86, 0.6)",
"HIGH_COMPILE_QUERIES": "rgba(255, 99, 71, 0.6)",
"OVER_PROVISIONED_QUERIES": "rgba(54, 162, 235, 0.6)",
},
"tooltip_fields": ["RECOMMENDATIONS"],
},
# Performance Issues Distribution
{
"chart_type": "pie",
"y_axis": [
"SELECT_STAR_QUERIES",
"UNPARTITIONED_SCAN_QUERIES",
"REPEATED_QUERIES",
"COMPLEX_JOIN_QUERIES",
"ZERO_RESULT_QUERIES",
"UNTAGGED_QUERIES"
],
"title": "Performance-Related Issues Distribution",
"colors": [
"rgba(75, 192, 192, 0.6)",
"rgba(153, 102, 255, 0.6)",
"rgba(255, 159, 64, 0.6)",
"rgba(199, 199, 199, 0.6)",
"rgba(83, 102, 255, 0.6)",
"rgba(144, 238, 144, 0.6)",
],
"tooltip_fields": ["RECOMMENDATIONS"],
}
],
"single_user_bad_practice_details": [
# Bad Practice Cost Impact
{
"chart_type": "horizontal_bar",
"x_axis": "COST_IMPACT",
"y_axis": "ISSUE_TYPE",
"title": "Cost Impact by Bad Practice Type",
"color_field": "ISSUE_TYPE",
"colors": {
"SELECT * Abuse": "rgba(255, 99, 132, 0.6)",
"Unpartitioned Scans": "rgba(54, 162, 235, 0.6)",
"Repeated Queries": "rgba(255, 206, 86, 0.6)",
"Complex Queries": "rgba(75, 192, 192, 0.6)",
},
"tooltip_fields": ["QUERY_COUNT", "RECOMMENDATION", "EXAMPLE_QUERY"],
},
# Query Count vs Cost Impact
{
"chart_type": "grouped_bar",
"x_axis": "ISSUE_TYPE",
"y_axis": ["QUERY_COUNT", "COST_IMPACT"],
"title": "Query Volume vs Cost Impact by Issue Type",
"colors": {
"QUERY_COUNT": "rgba(54, 162, 235, 0.6)",
"COST_IMPACT": "rgba(255, 99, 132, 0.6)",
},
"tooltip_fields": ["RECOMMENDATION", "EXAMPLE_QUERY"],
}
],
"single_user_critical_bad_practices_pie": [
{
"chart_type": "donut",
"x_axis": "ISSUE_TYPE",
"y_axis": "COST_IMPACT",
"title": "Critical Bad Practices Cost Distribution",
"colors": [
"rgba(255, 99, 132, 0.6)",
"rgba(54, 162, 235, 0.6)",
"rgba(255, 206, 86, 0.6)",
"rgba(75, 192, 192, 0.6)",
],
"tooltip_fields": ["COST_IMPACT"],
}
],
"credits_query_efficiency_trend": [
# Daily Credit Usage Trend
{
"chart_type": "line",
"x_axis": "USAGE_DATE",
"y_axis": "DAILY_CREDITS",
"title": "Daily Credit Consumption Trend",
"color_field": "DAILY_USAGE_STATUS",
"colors": {
"Very High": "rgba(255, 99, 132, 0.8)",
"High": "rgba(255, 206, 86, 0.8)",
"Normal": "rgba(54, 162, 235, 0.8)",
},
"tooltip_fields": ["QUERY_COUNT", "AVG_CREDITS_PER_QUERY", "QUERY_EFFICIENCY_STATUS"],
},
# Query Efficiency Over Time
{
"chart_type": "bar",
"x_axis": "USAGE_DATE",
"y_axis": "AVG_CREDITS_PER_QUERY",
"title": "Query Efficiency Trend (Credits per Query)",
"color_field": "QUERY_EFFICIENCY_STATUS",
"colors": {
"Inefficient": "rgba(255, 99, 132, 0.6)",
"Efficient": "rgba(54, 162, 235, 0.6)",
},
"tooltip_fields": ["QUERY_COUNT", "DAILY_CREDITS", "DAILY_USAGE_STATUS"],
},
# Combined View: Volume vs Efficiency
{
"chart_type": "combo",
"x_axis": "USAGE_DATE",
"y_axis": ["QUERY_COUNT", "AVG_CREDITS_PER_QUERY"],
"chart_types": ["bar", "line"],
"title": "Query Volume vs Efficiency Over Time",
"colors": {
"QUERY_COUNT": "rgba(54, 162, 235, 0.6)",
"AVG_CREDITS_PER_QUERY": "rgba(255, 99, 132, 0.8)",
},
"tooltip_fields": ["DAILY_CREDITS", "DAILY_USAGE_STATUS", "QUERY_EFFICIENCY_STATUS"],
}
],
"bytes_scanned_vs_rows_returned": [
# Efficiency Status Summary
{
"chart_type": "bar",
"x_axis": "EFFICIENCY_STATUS",
"y_axis": "MB_SCANNED",
"title": "Data Scanning Efficiency Analysis",
"color_field": "EFFICIENCY_STATUS",
"colors": {
"Inefficient": "rgba(255, 99, 132, 0.6)",
"Efficient": "rgba(54, 162, 235, 0.6)",
},
"tooltip_fields": ["ROWS_RETURNED", "MB_PER_ROW"],
},
# Detailed Query Analysis (Top Inefficient Queries)
{
"chart_type": "horizontal_bar",
"x_axis": "MB_PER_ROW",
"y_axis": "QUERY_ID",
"title": "Top Inefficient Queries (MB per Row)",
"color_field": "EFFICIENCY_STATUS",
"colors": {
"Inefficient": "rgba(255, 99, 132, 0.6)",
"Efficient": "rgba(54, 162, 235, 0.6)",
},
"tooltip_fields": ["MB_SCANNED", "ROWS_RETURNED"],
"limit": 20 # Show top 20 most inefficient queries
}
],
# Additional single user charts for comprehensive analysis
"single_user_time_analysis": [
# Peak Hour Analysis
{
"chart_type": "bar",
"x_axis": "HOUR_OF_DAY",
"y_axis": "QUERY_COUNT",
"title": "Query Distribution by Hour of Day",
"color_field": "IS_PEAK_HOUR",
"colors": {
"Yes": "rgba(255, 99, 132, 0.6)",
"No": "rgba(54, 162, 235, 0.6)",
},
"tooltip_fields": ["AVG_CREDITS_PER_QUERY", "LONG_RUNNING_QUERIES"],
},
# Weekly Pattern Analysis
{
"chart_type": "line",
"x_axis": "DAY_OF_WEEK",
"y_axis": "DAILY_CREDITS",
"title": "Weekly Credit Usage Pattern",
"colors": {"line": "rgba(54, 162, 235, 0.8)"},
"tooltip_fields": ["QUERY_COUNT", "AVG_CREDITS_PER_QUERY"],
}
],
"single_user_warehouse_analysis": [
# Warehouse Usage Efficiency
{
"chart_type": "stacked_bar",
"x_axis": "WAREHOUSE_SIZE",
"y_axis": ["QUERY_COUNT", "OVER_PROVISIONED_QUERIES"],
"title": "Warehouse Usage vs Over-Provisioning",
"colors": {
"QUERY_COUNT": "rgba(54, 162, 235, 0.6)",
"OVER_PROVISIONED_QUERIES": "rgba(255, 99, 132, 0.6)",
},
"tooltip_fields": ["COST_IMPACT", "RECOMMENDATION"],
}
]
}
Armaan Khan
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