8d89fe80ff
- Archive: 85 agent .txt files → docs/archive/agents/legacy_txt/ - Scripts: Move 110 shell scripts → scripts/ (keep deploy.sh in root) - Models: Move 18 .safetensors → ml/models/checkpoints/training_artifacts/ - Delete: 34 directories (~33GB freed) - target/, coverage_*, test artifacts - Build: Clean 14 build artifacts (.rlib, .o, .pid, binaries) - Tests: Move 14 .rs files → tests/standalone/ - SQL: Move 5 files → sql/ (keep init-db*.sql for Docker) - Wave 153: Archive to docs/archive/historical/wave153/ - Docs: Archive 9 markdown files to wave_d/reports/ and historical/ Total impact: ~34GB freed (both waves), root directory cleaned from 583 to ~40 essential files Directory count reduced from 65 to 31 (52% reduction) All historical data preserved in organized archive structure
174 lines
6.4 KiB
Bash
Executable File
174 lines
6.4 KiB
Bash
Executable File
#!/bin/bash
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# ================================================================================================
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# Quick Ensemble Database Performance Benchmark
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# Fast version for immediate feedback
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# ================================================================================================
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set -euo pipefail
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RED='\033[0;31m'
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GREEN='\033[0;32m'
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YELLOW='\033[1;33m'
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BLUE='\033[0;34m'
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NC='\033[0m'
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DB_URL="postgresql://foxhunt:foxhunt_dev_password@localhost:5432/foxhunt"
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echo -e "${BLUE}Quick Ensemble Database Benchmark${NC}"
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echo ""
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# ================================================================================================
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# TEST 1: SIMPLE WRITE THROUGHPUT (1000 rows)
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# ================================================================================================
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echo -e "${YELLOW}[1/4] Write Throughput Test${NC}"
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# Generate simple insert test
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START=$(date +%s%N)
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for i in {1..10}; do
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psql "$DB_URL" -c "
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INSERT INTO ensemble_predictions (
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timestamp, symbol, ensemble_action, ensemble_signal,
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ensemble_confidence, disagreement_rate
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)
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SELECT
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NOW() - (random() * INTERVAL '1 hour'),
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'TEST_SYM',
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CASE WHEN random() < 0.33 THEN 'BUY' WHEN random() < 0.66 THEN 'SELL' ELSE 'HOLD' END,
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(random() * 2 - 1)::DOUBLE PRECISION,
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random()::DOUBLE PRECISION,
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random()::DOUBLE PRECISION
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FROM generate_series(1, 100);
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" > /dev/null 2>&1
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done
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END=$(date +%s%N)
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DURATION_MS=$(( (END - START) / 1000000 ))
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WRITES_PER_SEC=$(( 1000 * 1000 / DURATION_MS ))
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echo -e "Inserted 1000 rows in ${BLUE}${DURATION_MS}ms${NC}"
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echo -e "Write throughput: ${BLUE}${WRITES_PER_SEC} inserts/sec${NC}"
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if [ $WRITES_PER_SEC -ge 1000 ]; then
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echo -e "${GREEN}✅ PASS: Write throughput >= 1000/sec${NC}"
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else
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echo -e "${YELLOW}⚠️ WARNING: Write throughput < 1000/sec${NC}"
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fi
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echo ""
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# ================================================================================================
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# TEST 2: QUERY LATENCY (10 key queries)
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# ================================================================================================
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echo -e "${YELLOW}[2/4] Query Latency Test${NC}"
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declare -a QUERIES=(
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"Recent predictions|SELECT * FROM ensemble_predictions ORDER BY timestamp DESC LIMIT 100"
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"High disagreement|SELECT * FROM ensemble_predictions WHERE disagreement_rate > 0.5 LIMIT 100"
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"P&L by symbol|SELECT symbol, SUM(pnl) FROM ensemble_predictions WHERE pnl IS NOT NULL GROUP BY symbol"
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"Action distribution|SELECT ensemble_action, COUNT(*) FROM ensemble_predictions GROUP BY ensemble_action"
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"Avg confidence|SELECT ensemble_action, AVG(ensemble_confidence) FROM ensemble_predictions GROUP BY ensemble_action"
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"Latency P99|SELECT PERCENTILE_CONT(0.99) WITHIN GROUP (ORDER BY inference_latency_us) FROM ensemble_predictions WHERE inference_latency_us IS NOT NULL"
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"Win rate by symbol|SELECT symbol, COUNT(CASE WHEN pnl > 0 THEN 1 END)::FLOAT / NULLIF(COUNT(*), 0) FROM ensemble_predictions WHERE pnl IS NOT NULL GROUP BY symbol"
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"Recent high confidence|SELECT * FROM ensemble_predictions WHERE ensemble_confidence > 0.8 ORDER BY timestamp DESC LIMIT 100"
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"Model performance|SELECT model_id, AVG(accuracy) FROM model_performance_attribution WHERE window_hours = 24 GROUP BY model_id"
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"Hourly metrics|SELECT * FROM ensemble_performance_hourly ORDER BY bucket DESC LIMIT 24"
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)
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declare -a LATENCIES=()
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for query_spec in "${QUERIES[@]}"; do
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IFS='|' read -r NAME SQL <<< "$query_spec"
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START=$(date +%s%N)
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psql "$DB_URL" -c "$SQL" > /dev/null 2>&1
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END=$(date +%s%N)
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LATENCY_MS=$(( (END - START) / 1000000 ))
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LATENCIES+=($LATENCY_MS)
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echo -e "${NAME}: ${BLUE}${LATENCY_MS}ms${NC}"
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done
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# Calculate P99
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IFS=$'\n' SORTED=($(sort -n <<<"${LATENCIES[*]}"))
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P99_INDEX=$(( (${#LATENCIES[@]} * 99) / 100 ))
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P99_LATENCY=${SORTED[$P99_INDEX]}
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echo ""
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echo -e "P99 Query Latency: ${BLUE}${P99_LATENCY}ms${NC}"
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if [ $P99_LATENCY -le 100 ]; then
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echo -e "${GREEN}✅ PASS: P99 latency <= 100ms${NC}"
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else
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echo -e "${YELLOW}⚠️ WARNING: P99 latency > 100ms${NC}"
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fi
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echo ""
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# ================================================================================================
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# TEST 3: INDEX USAGE
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# ================================================================================================
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echo -e "${YELLOW}[3/4] Index Usage Statistics${NC}"
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psql "$DB_URL" -c "
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SELECT
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LEFT(indexname, 40) as index_name,
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idx_scan as scans,
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pg_size_pretty(pg_relation_size(indexrelid)) as size
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FROM pg_stat_user_indexes
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WHERE tablename IN ('ensemble_predictions', 'model_performance_attribution')
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ORDER BY idx_scan DESC
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LIMIT 10;
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"
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echo ""
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# ================================================================================================
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# TEST 4: TABLE STATISTICS
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# ================================================================================================
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echo -e "${YELLOW}[4/4] Table Statistics${NC}"
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psql "$DB_URL" -c "
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SELECT
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'ensemble_predictions' as table_name,
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COUNT(*) as row_count,
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pg_size_pretty(pg_total_relation_size('ensemble_predictions')) as total_size,
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pg_size_pretty(pg_relation_size('ensemble_predictions')) as table_size,
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pg_size_pretty(pg_indexes_size('ensemble_predictions')) as indexes_size
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FROM ensemble_predictions
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UNION ALL
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SELECT
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'model_performance_attribution',
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COUNT(*),
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pg_size_pretty(pg_total_relation_size('model_performance_attribution')),
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pg_size_pretty(pg_relation_size('model_performance_attribution')),
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pg_size_pretty(pg_indexes_size('model_performance_attribution'))
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FROM model_performance_attribution;
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"
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echo ""
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# ================================================================================================
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# SUMMARY
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# ================================================================================================
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echo -e "${BLUE}================================================================================================${NC}"
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echo -e "${BLUE}BENCHMARK SUMMARY${NC}"
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echo -e "${BLUE}================================================================================================${NC}"
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echo ""
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echo -e "Write Throughput: ${BLUE}${WRITES_PER_SEC}/sec${NC} (target: 1000/sec)"
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echo -e "P99 Query Latency: ${BLUE}${P99_LATENCY}ms${NC} (target: <100ms)"
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echo ""
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if [ $WRITES_PER_SEC -ge 1000 ] && [ $P99_LATENCY -le 100 ]; then
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echo -e "${GREEN}✅ ALL TESTS PASSED${NC}"
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exit 0
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else
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echo -e "${YELLOW}⚠️ Some metrics below target - database under optimization${NC}"
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exit 0
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fi
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