#!/bin/bash
# This script packages up the importer as it exists in the current git repo,
# creates a bunch of GCE VMs, and runs the importer there on all cities, using
# static sharding.
#
# This process is only runnable by Dustin, due to current GCE/EC2 permissions.
#
# Run from the repo's root dir: cloud/start_batch_import.sh

set -e
set -x

EXPERIMENT_TAG=$1
if [ "$EXPERIMENT_TAG" == "" ]; then
	echo Missing args;
	exit 1;
fi

NUM_WORKERS=10
ZONE=us-east1-b
# See other options: https://cloud.google.com/compute/docs/machine-types
# Particularly... e2-standard-2, n2-standard-2, c2-standard-4
MACHINE_TYPE=e2-standard-2
# All of data/ is currently around 30GB
DISK_SIZE=40GB
# Compressing and checksumming gigantic files needs more IOPS
DISK_TYPE=pd-ssd
# Haha, using a project from college, my last traffic sim...
PROJECT=aorta-routes

function build_payload {
	# It's a faster workflow to copy the local binaries into the VMs, rather than
	# build them there. But it does require us to build the importer without the
	# GDAL bindings, since the dynamic linking won't transfer over to the VM due to
	# the GDAL version being different.
	#
	# GDAL bindings are only used when initially building popdat.bin for Seatle;
	# there's almost never a need to regenerate this, and it can be done locally
	# when required.
	cargo build --release --bin importer --bin updater

	# Build our payload for the VMs
	# This mkdir deliberately fails if the directory is already there; it probably
	# means the last run broke somehow
	mkdir worker_payload
	mkdir -p worker_payload/target/release
	cp target/release/importer worker_payload/target/release/
	cp target/release/updater worker_payload/target/release/
	mkdir worker_payload/data
	cp data/MANIFEST.json worker_payload/data
	mkdir worker_payload/importer
	cp -Rv importer/config worker_payload/importer
	cp cloud/worker_script.sh worker_payload/
	# Copy in AWS credentials! Obviously don't go making worker_payload/ public or
	# letting anybody into the VMs.
	#
	# Alternatively, I could just scp the files from the VMs back to my local
	# computer. But more than likely, GCE's upstream speed to S3 (even
	# cross-region) is better than Comcast. :)
	cp -Rv ~/.aws worker_payload/
	zip -r worker_payload worker_payload
}

function create_vms {
	# Ideally we'd use the bulk API, but someone's not on top of those
	# gcloud integration tests...
	# https://issuetracker.google.com/issues/188462253
	for ((i = 0; i < $NUM_WORKERS; i++)); do
		gcloud compute \
			--project=$PROJECT \
			instances create "worker-$i" \
			--zone=$ZONE \
			--machine-type=$MACHINE_TYPE \
			--boot-disk-size=$DISK_SIZE \
			--boot-disk-type=$DISK_TYPE \
			--image-family=ubuntu-2004-lts \
			--image-project=ubuntu-os-cloud \
			--scopes=compute-rw
	done

	# There's a funny history behind the whole "how do I wait for my VM to be
	# SSHable?" question...
	sleep 30s
}

function start_workers {
	for ((i = 0; i < $NUM_WORKERS; i++)); do
		gcloud compute scp \
			--project=$PROJECT \
			--zone=$ZONE \
			worker_payload.zip \
			worker-$i:~/worker_payload.zip
		gcloud compute ssh \
			--project=$PROJECT \
			--zone=$ZONE \
			worker-$i \
			--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 &"
	done
}

build_payload
create_vms
start_workers

# To follow along with a worker:
# > gcloud compute ssh worker-5 --command='tail -f logs'
#
# To see which workers are still running (or have failed):
# > gcloud compute instances list