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https://github.com/featurebasedb/featurebase.git
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0f67a0c432
- had to make sure we don't snapshot until directive is fully applied
on a computer... otherwise there's races between loading the files and
truncating the write log.
- added a dirty bit to resources and a bool return to incrementing the
write log... don't snapshot if it returns false because that means
there's been no writes. (but make sure you close the storage transaction!)
- added the actually snapshotting routine which just fires every
<timeout> and serially snapshots everything.
- tweaked some logging
- added ability to get all tables in an org/db or literally all. I
think I just needed the "literally all", but it was natural to allow
it to be scoped to org or DB as well.
(cherry picked from commit b8b08bc9eb)
91 lines
2.5 KiB
Makefile
91 lines
2.5 KiB
Makefile
.PHONY: test testv test-integration testv-integration
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MCLOUD_ENV ?= sandbox
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MCLOUD_ENV_FILE=.env.$(MCLOUD_ENV)
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-include $(MCLOUD_ENV_FILE)
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GO=go
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test:
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$(GO) test ./... -short
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testv:
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$(GO) test -v ./... -short
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test-integration:
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mkdir -p ../coverage-from-docker
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$(GO) test ./test/dax -count 1 -run TestDAXIntegration/$(RUN)
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testv-integration:
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$(GO) test -v ./test/dax -count 1 -run TestDAXIntegration/$(RUN)
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############################### AWS STUFF ###############################
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AWS_REGION ?=
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AWS_PROFILE ?=
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AWS = aws --profile=$(AWS_PROFILE) --region=$(AWS_REGION)
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# After pushing new images, use "make redeploy-ecs" to redeploy all DAX services.
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redeploy-ecs: redeploy-svc-mds redeploy-svc-computer redeploy-svc-queryer
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redeploy-svc-%:
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$(AWS) ecs update-service --cluster DAX --service $*-$(MCLOUD_ENV)-ecs-service --force-new-deployment --no-cli-pager
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# Scale changes the desired count of the computer service. e.g. "make scale N=4"
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scale:
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$(AWS) ecs update-service --cluster DAX --service computer-$(MCLOUD_ENV)-ecs-service --desired-count=$(N) --no-cli-pager
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I ?= 0
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# Get a shell on a running contianer. e.g. "make mds-shell", "make datagen-shell", etc.
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%-shell:
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$(eval TASK_ARN := $(shell $(AWS) ecs list-tasks --cluster=DAX --family=$*-family | jq -r .taskArns[$(I)]))
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$(AWS) ecs execute-command --cluster=DAX --task=$(TASK_ARN) --command=/bin/sh --interactive
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datagen: task-arn-datagen
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$(eval TASK_ARN := $(shell $(AWS) ecs list-tasks --cluster=DAX --family=$*-family | jq -r .taskArns[$(I)]))
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$(AWS) ecs run-task --cluster=DAX --task-definition=$(TASK_ARN) --cli-input-json=file://./datagen_task_input.json --no-cli-pager --enable-execute-command
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####################### docker-compose stuff ##############################3
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dc-reset: dc-prereqs dc-down
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rm -rf ./dax-data/{snapshotter,writelogger}/*
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dc-build:
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cd .. && $(MAKE) build-for-quick
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docker-compose build
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dc-up:
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docker-compose up -d
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dc-down:
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docker-compose down
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dc-full-reup: dc-reset dc-build dc-up
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dc-logs:
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docker-compose logs -f
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dc-logs-%:
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docker-compose logs -f $*
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dc-prereqs:
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mkdir -p ../.quick
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dc-cli:
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featurebase cli --host localhost --port 8080 --org-id=testorg --db-id=testdb
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# This is just an example. For it to work, you'll first need to:
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# featurebase cli --host localhost --port 8080 --org-id=testorg --db-id=testdb
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# create table keysidstbl2 (_id string, slice idset);
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dc-datagen:
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docker-compose run datagen --end-at=500 --pilosa.batch-size=500 --featurebase.table-name=keysidstbl2
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dc-exec-%:
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docker-compose exec $* /bin/sh
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