#!/bin/bash

#

# Usage (to test): $ SMOKE=true bash scripts/bench.bash

#

# - `SMOKE`: Run benchmarks quickly but not representative

#

set -ex

# Clean-up old results

if [ "$SMOKE" = "" ]; then

rm -rf gh-pages

fi

NEXMARK_CSV_FILE='nexmark_results.csv'

NEXMARK_DRAM_CSV_FILE='dram_nexmark_results.csv'

NEXMARK_SQL_CSV_FILE='sql_nexmark_results.csv'

NEXMARK_SQL_METRICS_CSV_FILE='sql_nexmark_metrics.csv'

NEXMARK_SQL_STORAGE_CSV_FILE='sql_storage_nexmark_results.csv'

NEXMARK_SQL_STORAGE_METRICS_CSV_FILE='sql_storage_nexmark_metrics.csv'

NEXMARK_PERSISTENCE_CSV_FILE='persistence_nexmark_results.csv'

GALEN_CSV_FILE='galen_results.csv'

LDBC_CSV_FILE='ldbc_results.csv'

rm -f crates/nexmark/${NEXMARK_CSV_FILE} crates/nexmark/${NEXMARK_SQL_CSV_FILE} crates/dbsp/${GALEN_CSV_FILE} crates/dbsp/${LDBC_CSV_FILE} crates/nexmark/${NEXMARK_DRAM_CSV_FILE} crates/nexmark/${NEXMARK_PERSISTENCE_CSV_FILE}

# Run nexmark benchmark

EVENT_RATE=10000000

MAX_EVENTS=100000000

GENERATORS=8

CORES=6

if [ "$SMOKE" != "" ]; then

EVENT_RATE=10000000

MAX_EVENTS=1000000

fi

FILES=( "q0" "q1" "q2" "q3" "q4" "q5" "q6" "q7" "q8" "q9" "q12" "q13" "q14" "q15" "q16" "q17" "q18" "q19" "q20" "q21" "q22" )

for FILE in "${FILES[@]}"

do cargo bench --bench nexmark -- --first-event-rate=${EVENT_RATE} --max-events=${MAX_EVENTS} --cpu-cores ${CORES} --num-event-generators ${GENERATORS} --source-buffer-size 10000 --input-batch-size 40000 --csv ${NEXMARK_CSV_FILE} --query $FILE

done

# Run nexmark SQL benchmark

# This test requires a running instance of redpanda and pipeline-manager.

# The Earthfile should run those.

# 100M events causes out of memory problems with SQL tests

MAX_EVENTS=10000000

if [ "$SMOKE" != "" ]; then

MAX_EVENTS=1000000

fi

KAFKA_BROKER=localhost:9092

rpk topic -X brokers=$KAFKA_BROKER delete bid auction person

cargo run -p dbsp_nexmark --example generate --features with-kafka -- --max-events ${MAX_EVENTS} -O bootstrap.servers=$KAFKA_BROKER

FELDERA_API=http://localhost:8080

python3 benchmark/feldera-sql/run.py --api-url $FELDERA_API -O bootstrap.servers=$KAFKA_BROKER --csv crates/nexmark/${NEXMARK_SQL_CSV_FILE} --csv-metrics crates/nexmark/${NEXMARK_SQL_METRICS_CSV_FILE} --metrics-interval 1

rpk topic -X brokers=$KAFKA_BROKER delete bid auction person

cargo run -p dbsp_nexmark --example generate --features with-kafka -- --max-events ${MAX_EVENTS} -O bootstrap.servers=$KAFKA_BROKER

FELDERA_API=http://localhost:8080

python3 benchmark/feldera-sql/run.py --storage --api-url $FELDERA_API -O bootstrap.servers=$KAFKA_BROKER --csv crates/nexmark/${NEXMARK_SQL_STORAGE_CSV_FILE} --csv-metrics crates/nexmark/${NEXMARK_SQL_STORAGE_METRICS_CSV_FILE} --metrics-interval 1

# Run galen benchmark

cargo bench --bench galen -- --workers 10 --csv ${GALEN_CSV_FILE}

# Run ldbc benchmarks

DATASET_SMALL='graph500-22'

DATASET_MEDIUM='datagen-8_4-fb'

if [ "$SMOKE" != "" ]; then

DATASET_SMALL='wiki-Talk'

DATASET_MEDIUM='kgs'

fi

#cargo bench --bench ldbc-graphalytics -- bfs ${DATASET_SMALL} --threads 1 --csv ${LDBC_CSV_FILE}

#cargo bench --bench ldbc-graphalytics -- bfs ${DATASET_MEDIUM} --threads 6 --csv ${LDBC_CSV_FILE}

#cargo bench --bench ldbc-graphalytics -- pagerank ${DATASET_SMALL} --threads 1 --csv ${LDBC_CSV_FILE}

#cargo bench --bench ldbc-graphalytics -- pagerank ${DATASET_MEDIUM} --threads 6 --csv ${LDBC_CSV_FILE}

# Run nexmark benchmark with persistence

EVENT_RATE=5000000

MAX_EVENTS=3000000

CORES=1

if [ "$SMOKE" != "" ]; then

EVENT_RATE=5000000

MAX_EVENTS=100000

fi

cargo bench --bench nexmark -- --first-event-rate=${EVENT_RATE} --max-events=${MAX_EVENTS} --cpu-cores ${CORES} --num-event-generators 6 --source-buffer-size 10000 --input-batch-size 40000 --csv ${NEXMARK_DRAM_CSV_FILE}

#cargo bench --bench nexmark --features persistence -- --first-event-rate=${EVENT_RATE} --max-events=${MAX_EVENTS} --cpu-cores ${CORES} --num-event-generators 6 --source-buffer-size 10000 --input-batch-size 40000 --csv ${NEXMARK_PERSISTENCE_CSV_FILE}