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https://github.com/a-b-street/abstreet.git
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123 lines
3.9 KiB
Bash
Executable File
123 lines
3.9 KiB
Bash
Executable File
#!/bin/bash
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# This script packages up the importer as it exists in the current git repo,
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# creates a bunch of GCE VMs, and runs the importer there on all cities, using
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# static sharding.
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#
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# This process is only runnable by Dustin, due to current GCE/S3 permissions.
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#
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# Run from the repo's root dir: cloud/start_batch_import.sh
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set -e
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set -x
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EXPERIMENT_TAG=$1
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if [ "$EXPERIMENT_TAG" == "" ]; then
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echo Missing args;
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exit 1;
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fi
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if [ "$2" != "gcs_sync_done" ]; then
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echo First go sync dev/data/input from S3 to GCS. https://console.cloud.google.com/transfer/cloud/jobs
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exit 1;
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fi
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NUM_WORKERS=10
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ZONE=us-east1-b
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# See other options: https://cloud.google.com/compute/docs/machine-types
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# Particularly... e2-standard-2, n2-standard-2, c2-standard-4
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SMALL_MACHINE_TYPE=e2-standard-2
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LARGE_MACHINE_TYPE=c2-standard-4
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# All of data/ is currently around 30GB
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DISK_SIZE=40GB
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# Compressing and checksumming gigantic files needs more IOPS
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# TODO But wait, e2-standard-2 doesn't support local PD?!
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DISK_TYPE=pd-ssd
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# Haha, using a project from college, my last traffic sim...
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PROJECT=aorta-routes
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function build_payload {
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# It's a faster workflow to copy the local binaries into the VMs, rather than
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# build them there.
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cargo build --release --bin updater -- download
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# This is needed to regenerate popdat.bin for Seattle. It requires the
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# VMs to have a matching GDAL version. Since the VM runs the same
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# version of Ubuntu as I do locally, this works out fine.
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cargo build --release --bin cli --features importer/scenarios
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# Build our payload for the VMs
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# This mkdir deliberately fails if the directory is already there; it probably
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# means the last run broke somehow
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mkdir worker_payload
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mkdir -p worker_payload/target/release
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cp target/release/cli worker_payload/target/release/cli
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cp target/release/updater worker_payload/target/release/
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mkdir worker_payload/data
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cp data/MANIFEST.json worker_payload/data
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mkdir worker_payload/importer
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cp -Rv importer/config worker_payload/importer
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cp cloud/worker_script.sh worker_payload/
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# Copy in AWS credentials! Obviously don't go making worker_payload/ public or
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# letting anybody into the VMs.
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#
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# Alternatively, I could just scp the files from the VMs back to my local
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# computer. But more than likely, GCE's upstream speed to S3 (even
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# cross-region) is better than Comcast. :)
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cp -Rv ~/.aws worker_payload/
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zip -r worker_payload worker_payload
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}
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function create_vms {
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# Ideally we'd use the bulk API, but someone's not on top of those
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# gcloud integration tests...
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# https://issuetracker.google.com/issues/188462253
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for ((i = 0; i < $NUM_WORKERS; i++)); do
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# The first shard always handles Seattle, which needs more than
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# 8GB of memory. Just give it really hefty hardware.
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if [ $i == 0 ]; then
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machine_type=$LARGE_MACHINE_TYPE;
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else
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machine_type=$SMALL_MACHINE_TYPE;
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fi
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gcloud compute \
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--project=$PROJECT \
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instances create "worker-$i" \
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--zone=$ZONE \
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--machine-type=$machine_type \
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--boot-disk-size=$DISK_SIZE \
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--boot-disk-type=$DISK_TYPE \
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--image-family=ubuntu-2004-lts \
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--image-project=ubuntu-os-cloud \
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--scopes=compute-rw,storage-ro
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done
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# There's a funny history behind the whole "how do I wait for my VM to be
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# SSHable?" question...
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sleep 30s
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}
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function start_workers {
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for ((i = 0; i < $NUM_WORKERS; i++)); do
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gcloud compute scp \
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--project=$PROJECT \
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--zone=$ZONE \
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worker_payload.zip \
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worker-$i:~/worker_payload.zip
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gcloud compute ssh \
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--project=$PROJECT \
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--zone=$ZONE \
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worker-$i \
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--command="sudo apt-get -qq install -y unzip; unzip -q worker_payload.zip; ./worker_payload/worker_script.sh $EXPERIMENT_TAG $i $NUM_WORKERS 1> logs 2>&1 &"
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done
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}
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build_payload
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create_vms
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start_workers
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# To follow along with a worker:
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# > gcloud compute ssh worker-5 --command='tail -f logs'
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#
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# To see which workers are still running (or have failed):
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# > gcloud compute instances list
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