milvus/Makefile

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# Copyright (C) 2019-2020 Zilliz. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software distributed under the License
# is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
# or implied. See the License for the specific language governing permissions and limitations under the License.
GO ?= go
PWD := $(shell pwd)
GOPATH := $(shell $(GO) env GOPATH)
SHELL := /bin/bash
OBJPREFIX := "github.com/milvus-io/milvus/cmd/milvus"
MILVUS_GO_BUILD_TAGS := "dynamic,sonic"
INSTALL_PATH := $(PWD)/bin
LIBRARY_PATH := $(PWD)/lib
Upgrade go from 1.20 to 1.21 (#33047) Signed-off-by: shaoting-huang [shaoting-huang@zilliz.com] issue: https://github.com/milvus-io/milvus/issues/32982 # Background Go 1.21 introduces several improvements and changes over Go 1.20, which is quite stable now. According to [Go 1.21 Release Notes](https://tip.golang.org/doc/go1.21), the big difference of Go 1.21 is enabling Profile-Guided Optimization by default, which can improve performance by around 2-14%. Here are the summary steps of PGO: 1. Build Initial Binary (Without PGO) 2. Deploying the Production Environment 3. Run the program and collect Performance Analysis Data (CPU pprof) 4. Analyze the Collected Data and Select a Performance Profile for PGO 5. Place the Performance Analysis File in the Main Package Directory and Name It default.pgo 6. go build Detects the default.pgo File and Enables PGO 7. Build and Release the Updated Binary (With PGO) 8. Iterate and Repeat the Above Steps <img width="657" alt="Screenshot 2024-05-14 at 15 57 01" src="https://github.com/milvus-io/milvus/assets/167743503/b08d4300-0be1-44dc-801f-ce681dabc581"> # What does this PR do There are three experiments, search benchmark by Zilliz test platform, search benchmark by open-source [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file), and search benchmark with PGO. We do both search benchmarks by Zilliz test platform and by VectorDBBench to reduce reliance on a single experimental result. Besides, we validate the performance enhancement with PGO. ## Search Benchmark Report by Zilliz Test Platform An upgrade to Go 1.21 was conducted on a Milvus Standalone server, equipped with 16 CPUs and 64GB of memory. The search performance was evaluated using a 1 million entry local dataset with an L2 metric type in a 768-dimensional space. The system was tested for concurrent searches with 50 concurrent tasks for 1 hour, each with a 20-second interval. The reason for using one server rather than two servers to compare is to guarantee the same data source and same segment state after compaction. Test Sequence: 1. Go 1.20 Initial Run: Insert data, build index, load index, and search. 2. Go 1.20 Rebuild: Rebuild the index with the same dataset, load index, and search. 3. Go 1.21 Load: Upload to Go 1.21 within the server. Then load the index from the second run, and search. 4. Go 1.21 Rebuild: Rebuild the index with the same dataset, load index, and search. Search Metrics: | Metric | Go 1.20 | Go 1.20 Rebuild Index | Go 1.21 | Go 1.21 Rebuild Index | |----------------------------|------------------|-----------------|------------------|-----------------| | `search requests` | 10,942,683 | 16,131,726 | 16,200,887 | 16,331,052 | | `search fails` | 0 | 0 | 0 | 0 | | `search RT_avg` (ms) | 16.44 | 11.15 | 11.11 | 11.02 | | `search RT_min` (ms) | 1.30 | 1.28 | 1.31 | 1.26 | | `search RT_max` (ms) | 446.61 | 233.22 | 235.90 | 147.93 | | `search TP50` (ms) | 11.74 | 10.46 | 10.43 | 10.35 | | `search TP99` (ms) | 92.30 | 25.76 | 25.36 | 25.23 | | `search RPS` | 3,039 | 4,481 | 4,500 | 4,536 | ### Key Findings The benchmark tests reveal that the index build time with Go 1.20 at 340.39 ms and Go 1.21 at 337.60 ms demonstrated negligible performance variance in index construction. However, Go 1.21 offers slightly better performance in search operations compared to Go 1.20, with improvements in handling concurrent tasks and reducing response times. ## Search Benchmark Report By VectorDb Bench Follow [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file) to create a VectorDb Bench test for Go 1.20 and Go 1.21. We test the search performance with Go 1.20 and Go 1.21 (without PGO) on the Milvus Standalone system. The tests were conducted using the Cohere dataset with 1 million entries in a 768-dimensional space, utilizing the COSINE metric type. Search Metrics: Metric | Go 1.20 | Go 1.21 without PGO -- | -- | -- Load Duration (seconds) | 1195.95 | 976.37 Queries Per Second (QPS) | 841.62 | 875.89 99th Percentile Serial Latency (seconds) | 0.0047 | 0.0076 Recall | 0.9487 | 0.9489 ### Key Findings Go 1.21 indicates faster index loading times and larger search QPS handling. ## PGO Performance Test Milvus has already added [net/http/pprof](https://pkg.go.dev/net/http/pprof) in the metrics. So we can curl the CPU profile directly by running `curl -o default.pgo "http://${MILVUS_SERVER_IP}:${MILVUS_SERVER_PORT}/debug/pprof/profile?seconds=${TIME_SECOND}"` to collect the profile as the default.pgo during the first search. Then I build Milvus with PGO and use the same index to run the search again. The result is as below: Search Metrics | Metric | Go 1.21 Without PGO | Go 1.21 With PGO | Change (%) | |---------------------------------------------|------------------|-----------------|------------| | `search Requests` | 2,644,583 | 2,837,726 | +7.30% | | `search Fails` | 0 | 0 | N/A | | `search RT_avg` (ms) | 11.34 | 10.57 | -6.78% | | `search RT_min` (ms) | 1.39 | 1.32 | -5.18% | | `search RT_max` (ms) | 349.72 | 143.72 | -58.91% | | `search TP50` (ms) | 10.57 | 9.93 | -6.05% | | `search TP99` (ms) | 26.14 | 24.16 | -7.56% | | `search RPS` | 4,407 | 4,729 | +7.30% | ### Key Findings PGO led to a notable enhancement in search performance, particularly in reducing the maximum response time by 58% and increasing the search QPS by 7.3%. ### Further Analysis Generate a diff flame graphs between two CPU profiles by running `go tool pprof -http=:8000 -diff_base nopgo.pgo pgo.pgo -normalize` <img width="1894" alt="goprofiling" src="https://github.com/milvus-io/milvus/assets/167743503/ab9e91eb-95c7-4963-acd9-d1c3c73ee010"> Further insight of HnswIndexNode and Milvus Search Handler <img width="1906" alt="hnsw" src="https://github.com/milvus-io/milvus/assets/167743503/a04cf4a0-7c97-4451-b3cf-98afc20a0b05"> <img width="1873" alt="search_handler" src="https://github.com/milvus-io/milvus/assets/167743503/5f4d3982-18dd-4115-8e76-460f7f534c7f"> After applying PGO to the Milvus server, the CPU utilization of the faiss::fvec_L2 function has decreased. This optimization significantly enhances the performance of the [HnswIndexNode::Search::searchKnn](https://github.com/zilliztech/knowhere/blob/e0c9c41aa22d8f6e6761a0a54460e4573de15bfe/src/index/hnsw/hnsw.cc#L203) method, which is frequently invoked by Knowhere during high-concurrency searches. As the explanation from Go release notes, the function might be more aggressively inlined by Go compiler during the second build with the CPU profiling collected from the first run. As a result, the search handler efficiency within Milvus DataNode has improved, allowing the server to process a higher number of search queries per second (QPS). # Conclusion The combination of Go 1.21 and PGO has led to substantial enhancements in search performance for Milvus server, particularly in terms of search QPS and response times, making it more efficient for handling high-concurrency search operations. Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
2024-05-22 13:21:39 +08:00
PGO_PATH := $(PWD)/configs/pgo
OS := $(shell uname -s)
mode = Release
use_disk_index = OFF
ifdef disk_index
use_disk_index = ${disk_index}
endif
use_asan = OFF
ifeq ($(USE_ASAN), ON)
use_asan = ${USE_ASAN}
CGO_LDFLAGS := $(shell go env CGO_LDFLAGS) -fno-stack-protector -fno-omit-frame-pointer -fno-var-tracking -fsanitize=address
CGO_CFLAGS := $(shell go env CGO_CFLAGS) -fno-stack-protector -fno-omit-frame-pointer -fno-var-tracking -fsanitize=address
MILVUS_GO_BUILD_TAGS := $(MILVUS_GO_BUILD_TAGS),use_asan
endif
use_dynamic_simd = ON
ifdef USE_DYNAMIC_SIMD
use_dynamic_simd = ${USE_DYNAMIC_SIMD}
endif
use_opendal = OFF
ifdef USE_OPENDAL
use_opendal = ${USE_OPENDAL}
endif
# golangci-lint
GOLANGCI_LINT_VERSION := 1.55.2
GOLANGCI_LINT_OUTPUT := $(shell $(INSTALL_PATH)/golangci-lint --version 2>/dev/null)
INSTALL_GOLANGCI_LINT := $(findstring $(GOLANGCI_LINT_VERSION), $(GOLANGCI_LINT_OUTPUT))
# mockery
MOCKERY_VERSION := 2.46.0
MOCKERY_OUTPUT := $(shell $(INSTALL_PATH)/mockery --version 2>/dev/null)
INSTALL_MOCKERY := $(findstring $(MOCKERY_VERSION),$(MOCKERY_OUTPUT))
# gci
GCI_VERSION := 0.11.2
GCI_OUTPUT := $(shell $(INSTALL_PATH)/gci --version 2>/dev/null)
INSTALL_GCI := $(findstring $(GCI_VERSION),$(GCI_OUTPUT))
# gofumpt
GOFUMPT_VERSION := 0.5.0
GOFUMPT_OUTPUT := $(shell $(INSTALL_PATH)/gofumpt --version 2>/dev/null)
INSTALL_GOFUMPT := $(findstring $(GOFUMPT_VERSION),$(GOFUMPT_OUTPUT))
# gotestsum
GOTESTSUM_VERSION := 1.11.0
GOTESTSUM_OUTPUT := $(shell $(INSTALL_PATH)/gotestsum --version 2>/dev/null)
INSTALL_GOTESTSUM := $(findstring $(GOTESTSUM_VERSION),$(GOTESTSUM_OUTPUT))
# protoc-gen-go
PROTOC_GEN_GO_VERSION := 1.33.0
PROTOC_GEN_GO_OUTPUT := $(shell echo | $(INSTALL_PATH)/protoc-gen-go --version 2>/dev/null)
INSTALL_PROTOC_GEN_GO := $(findstring $(PROTOC_GEN_GO_VERSION),$(PROTOC_GEN_GO_OUTPUT))
# protoc-gen-go-grpc
PROTOC_GEN_GO_GRPC_VERSION := 1.3.0
PROTOC_GEN_GO_GRPC_OUTPUT := $(shell echo | $(INSTALL_PATH)/protoc-gen-go-grpc --version 2>/dev/null)
INSTALL_PROTOC_GEN_GO_GRPC := $(findstring $(PROTOC_GEN_GO_GRPC_VERSION),$(PROTOC_GEN_GO_GRPC_OUTPUT))
index_engine = knowhere
export GIT_BRANCH=master
ifeq (${ENABLE_AZURE}, false)
AZURE_OPTION := -Z
endif
milvus: build-cpp print-build-info build-go
build-go:
@echo "Building Milvus ..."
@source $(PWD)/scripts/setenv.sh && \
mkdir -p $(INSTALL_PATH) && go env -w CGO_ENABLED="1" && \
CGO_LDFLAGS="$(CGO_LDFLAGS)" CGO_CFLAGS="$(CGO_CFLAGS)" GO111MODULE=on $(GO) build -pgo=$(PGO_PATH)/default.pgo -ldflags="-r $${RPATH} -X '$(OBJPREFIX).BuildTags=$(BUILD_TAGS)' -X '$(OBJPREFIX).BuildTime=$(BUILD_TIME)' -X '$(OBJPREFIX).GitCommit=$(GIT_COMMIT)' -X '$(OBJPREFIX).GoVersion=$(GO_VERSION)'" \
-tags $(MILVUS_GO_BUILD_TAGS) -o $(INSTALL_PATH)/milvus $(PWD)/cmd/main.go 1>/dev/null
milvus-gpu: build-cpp-gpu print-gpu-build-info
@echo "Building Milvus-gpu ..."
@source $(PWD)/scripts/setenv.sh && \
mkdir -p $(INSTALL_PATH) && go env -w CGO_ENABLED="1" && \
CGO_LDFLAGS="$(CGO_LDFLAGS)" CGO_CFLAGS="$(CGO_CFLAGS)" GO111MODULE=on $(GO) build -pgo=$(PGO_PATH)/default.pgo -ldflags="-r $${RPATH} -X '$(OBJPREFIX).BuildTags=$(BUILD_TAGS_GPU)' -X '$(OBJPREFIX).BuildTime=$(BUILD_TIME)' -X '$(OBJPREFIX).GitCommit=$(GIT_COMMIT)' -X '$(OBJPREFIX).GoVersion=$(GO_VERSION)'" \
-tags $(MILVUS_GO_BUILD_TAGS) -o $(INSTALL_PATH)/milvus $(PWD)/cmd/main.go 1>/dev/null
get-build-deps:
@(env bash $(PWD)/scripts/install_deps.sh)
# attention: upgrade golangci-lint should also change Dockerfiles in build/docker/builder/cpu/<os>
getdeps:
@mkdir -p $(INSTALL_PATH)
@if [ -z "$(INSTALL_GOLANGCI_LINT)" ]; then \
echo "Installing golangci-lint into ./bin/" && curl -sSfL https://raw.githubusercontent.com/golangci/golangci-lint/master/install.sh | sh -s -- -b $(INSTALL_PATH) v${GOLANGCI_LINT_VERSION} ; \
else \
echo "golangci-lint v@$(GOLANGCI_LINT_VERSION) already installed"; \
fi
@if [ -z "$(INSTALL_MOCKERY)" ]; then \
echo "Installing mockery v$(MOCKERY_VERSION) to ./bin/" && GOBIN=$(INSTALL_PATH) go install github.com/vektra/mockery/v2@v$(MOCKERY_VERSION); \
else \
echo "Mockery v$(MOCKERY_VERSION) already installed"; \
fi
@if [ -z "$(INSTALL_GOTESTSUM)" ]; then \
echo "Install gotestsum v$(GOTESTSUM_VERSION) to ./bin/" && GOBIN=$(INSTALL_PATH) go install -ldflags="-X 'gotest.tools/gotestsum/cmd.version=$(GOTESTSUM_VERSION)'" gotest.tools/gotestsum@v$(GOTESTSUM_VERSION); \
else \
echo "gotestsum v$(GOTESTSUM_VERSION) already installed";\
fi
get-proto-deps:
@mkdir -p $(INSTALL_PATH) # make sure directory exists
@if [ -z "$(INSTALL_PROTOC_GEN_GO)" ]; then \
echo "install protoc-gen-go $(PROTOC_GEN_GO_VERSION) to $(INSTALL_PATH)" && GOBIN=$(INSTALL_PATH) go install google.golang.org/protobuf/cmd/protoc-gen-go@v$(PROTOC_GEN_GO_VERSION); \
else \
echo "protoc-gen-go@v$(PROTOC_GEN_GO_VERSION) already installed";\
fi
@if [ -z "$(INSTALL_PROTOC_GEN_GO_GRPC)" ]; then \
echo "install protoc-gen-go-grpc $(PROTOC_GEN_GO_GRPC_VERSION) to $(INSTALL_PATH)" && GOBIN=$(INSTALL_PATH) go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@v$(PROTOC_GEN_GO_GRPC_VERSION); \
else \
echo "protoc-gen-go-grpc@v$(PROTOC_GEN_GO_GRPC_VERSION) already installed";\
fi
tools/bin/revive: tools/check/go.mod
cd tools/check; \
Upgrade go from 1.20 to 1.21 (#33047) Signed-off-by: shaoting-huang [shaoting-huang@zilliz.com] issue: https://github.com/milvus-io/milvus/issues/32982 # Background Go 1.21 introduces several improvements and changes over Go 1.20, which is quite stable now. According to [Go 1.21 Release Notes](https://tip.golang.org/doc/go1.21), the big difference of Go 1.21 is enabling Profile-Guided Optimization by default, which can improve performance by around 2-14%. Here are the summary steps of PGO: 1. Build Initial Binary (Without PGO) 2. Deploying the Production Environment 3. Run the program and collect Performance Analysis Data (CPU pprof) 4. Analyze the Collected Data and Select a Performance Profile for PGO 5. Place the Performance Analysis File in the Main Package Directory and Name It default.pgo 6. go build Detects the default.pgo File and Enables PGO 7. Build and Release the Updated Binary (With PGO) 8. Iterate and Repeat the Above Steps <img width="657" alt="Screenshot 2024-05-14 at 15 57 01" src="https://github.com/milvus-io/milvus/assets/167743503/b08d4300-0be1-44dc-801f-ce681dabc581"> # What does this PR do There are three experiments, search benchmark by Zilliz test platform, search benchmark by open-source [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file), and search benchmark with PGO. We do both search benchmarks by Zilliz test platform and by VectorDBBench to reduce reliance on a single experimental result. Besides, we validate the performance enhancement with PGO. ## Search Benchmark Report by Zilliz Test Platform An upgrade to Go 1.21 was conducted on a Milvus Standalone server, equipped with 16 CPUs and 64GB of memory. The search performance was evaluated using a 1 million entry local dataset with an L2 metric type in a 768-dimensional space. The system was tested for concurrent searches with 50 concurrent tasks for 1 hour, each with a 20-second interval. The reason for using one server rather than two servers to compare is to guarantee the same data source and same segment state after compaction. Test Sequence: 1. Go 1.20 Initial Run: Insert data, build index, load index, and search. 2. Go 1.20 Rebuild: Rebuild the index with the same dataset, load index, and search. 3. Go 1.21 Load: Upload to Go 1.21 within the server. Then load the index from the second run, and search. 4. Go 1.21 Rebuild: Rebuild the index with the same dataset, load index, and search. Search Metrics: | Metric | Go 1.20 | Go 1.20 Rebuild Index | Go 1.21 | Go 1.21 Rebuild Index | |----------------------------|------------------|-----------------|------------------|-----------------| | `search requests` | 10,942,683 | 16,131,726 | 16,200,887 | 16,331,052 | | `search fails` | 0 | 0 | 0 | 0 | | `search RT_avg` (ms) | 16.44 | 11.15 | 11.11 | 11.02 | | `search RT_min` (ms) | 1.30 | 1.28 | 1.31 | 1.26 | | `search RT_max` (ms) | 446.61 | 233.22 | 235.90 | 147.93 | | `search TP50` (ms) | 11.74 | 10.46 | 10.43 | 10.35 | | `search TP99` (ms) | 92.30 | 25.76 | 25.36 | 25.23 | | `search RPS` | 3,039 | 4,481 | 4,500 | 4,536 | ### Key Findings The benchmark tests reveal that the index build time with Go 1.20 at 340.39 ms and Go 1.21 at 337.60 ms demonstrated negligible performance variance in index construction. However, Go 1.21 offers slightly better performance in search operations compared to Go 1.20, with improvements in handling concurrent tasks and reducing response times. ## Search Benchmark Report By VectorDb Bench Follow [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file) to create a VectorDb Bench test for Go 1.20 and Go 1.21. We test the search performance with Go 1.20 and Go 1.21 (without PGO) on the Milvus Standalone system. The tests were conducted using the Cohere dataset with 1 million entries in a 768-dimensional space, utilizing the COSINE metric type. Search Metrics: Metric | Go 1.20 | Go 1.21 without PGO -- | -- | -- Load Duration (seconds) | 1195.95 | 976.37 Queries Per Second (QPS) | 841.62 | 875.89 99th Percentile Serial Latency (seconds) | 0.0047 | 0.0076 Recall | 0.9487 | 0.9489 ### Key Findings Go 1.21 indicates faster index loading times and larger search QPS handling. ## PGO Performance Test Milvus has already added [net/http/pprof](https://pkg.go.dev/net/http/pprof) in the metrics. So we can curl the CPU profile directly by running `curl -o default.pgo "http://${MILVUS_SERVER_IP}:${MILVUS_SERVER_PORT}/debug/pprof/profile?seconds=${TIME_SECOND}"` to collect the profile as the default.pgo during the first search. Then I build Milvus with PGO and use the same index to run the search again. The result is as below: Search Metrics | Metric | Go 1.21 Without PGO | Go 1.21 With PGO | Change (%) | |---------------------------------------------|------------------|-----------------|------------| | `search Requests` | 2,644,583 | 2,837,726 | +7.30% | | `search Fails` | 0 | 0 | N/A | | `search RT_avg` (ms) | 11.34 | 10.57 | -6.78% | | `search RT_min` (ms) | 1.39 | 1.32 | -5.18% | | `search RT_max` (ms) | 349.72 | 143.72 | -58.91% | | `search TP50` (ms) | 10.57 | 9.93 | -6.05% | | `search TP99` (ms) | 26.14 | 24.16 | -7.56% | | `search RPS` | 4,407 | 4,729 | +7.30% | ### Key Findings PGO led to a notable enhancement in search performance, particularly in reducing the maximum response time by 58% and increasing the search QPS by 7.3%. ### Further Analysis Generate a diff flame graphs between two CPU profiles by running `go tool pprof -http=:8000 -diff_base nopgo.pgo pgo.pgo -normalize` <img width="1894" alt="goprofiling" src="https://github.com/milvus-io/milvus/assets/167743503/ab9e91eb-95c7-4963-acd9-d1c3c73ee010"> Further insight of HnswIndexNode and Milvus Search Handler <img width="1906" alt="hnsw" src="https://github.com/milvus-io/milvus/assets/167743503/a04cf4a0-7c97-4451-b3cf-98afc20a0b05"> <img width="1873" alt="search_handler" src="https://github.com/milvus-io/milvus/assets/167743503/5f4d3982-18dd-4115-8e76-460f7f534c7f"> After applying PGO to the Milvus server, the CPU utilization of the faiss::fvec_L2 function has decreased. This optimization significantly enhances the performance of the [HnswIndexNode::Search::searchKnn](https://github.com/zilliztech/knowhere/blob/e0c9c41aa22d8f6e6761a0a54460e4573de15bfe/src/index/hnsw/hnsw.cc#L203) method, which is frequently invoked by Knowhere during high-concurrency searches. As the explanation from Go release notes, the function might be more aggressively inlined by Go compiler during the second build with the CPU profiling collected from the first run. As a result, the search handler efficiency within Milvus DataNode has improved, allowing the server to process a higher number of search queries per second (QPS). # Conclusion The combination of Go 1.21 and PGO has led to substantial enhancements in search performance for Milvus server, particularly in terms of search QPS and response times, making it more efficient for handling high-concurrency search operations. Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
2024-05-22 13:21:39 +08:00
$(GO) build -pgo=$(PGO_PATH)/default.pgo -o ../bin/revive github.com/mgechev/revive
cppcheck:
@#(env bash ${PWD}/scripts/core_build.sh -l)
@(env bash ${PWD}/scripts/check_cpp_fmt.sh)
fmt:
ifdef GO_DIFF_FILES
@echo "Running $@ check"
@GO111MODULE=on env bash $(PWD)/scripts/gofmt.sh $(GO_DIFF_FILES)
else
@echo "Running $@ check"
@GO111MODULE=on env bash $(PWD)/scripts/gofmt.sh cmd/
@GO111MODULE=on env bash $(PWD)/scripts/gofmt.sh internal/
@GO111MODULE=on env bash $(PWD)/scripts/gofmt.sh tests/integration/
@GO111MODULE=on env bash $(PWD)/scripts/gofmt.sh tests/go/
@GO111MODULE=on env bash $(PWD)/scripts/gofmt.sh pkg/
endif
lint-fix: getdeps
@mkdir -p $(INSTALL_PATH)
@if [ -z "$(INSTALL_GCI)" ]; then \
echo "Installing gci v$(GCI_VERSION) to ./bin/" && GOBIN=$(INSTALL_PATH) go install github.com/daixiang0/gci@v$(GCI_VERSION); \
else \
echo "gci v$(GCI_VERSION) already installed"; \
fi
@if [ -z "$(INSTALL_GOFUMPT)" ]; then \
echo "Installing gofumpt v$(GOFUMPT_VERSION) to ./bin/" && GOBIN=$(INSTALL_PATH) go install mvdan.cc/gofumpt@v$(GOFUMPT_VERSION); \
else \
echo "gofumpt v$(GOFUMPT_VERSION) already installed"; \
fi
@echo "Running gofumpt fix"
@$(INSTALL_PATH)/gofumpt -l -w internal/
@$(INSTALL_PATH)/gofumpt -l -w cmd/
@$(INSTALL_PATH)/gofumpt -l -w pkg/
@$(INSTALL_PATH)/gofumpt -l -w client/
@$(INSTALL_PATH)/gofumpt -l -w tests/go_client/
@$(INSTALL_PATH)/gofumpt -l -w tests/integration/
@echo "Running gci fix"
@$(INSTALL_PATH)/gci write cmd/ --skip-generated -s standard -s default -s "prefix(github.com/milvus-io)" --custom-order
@$(INSTALL_PATH)/gci write internal/ --skip-generated -s standard -s default -s "prefix(github.com/milvus-io)" --custom-order
@$(INSTALL_PATH)/gci write pkg/ --skip-generated -s standard -s default -s "prefix(github.com/milvus-io)" --custom-order
@$(INSTALL_PATH)/gci write client/ --skip-generated -s standard -s default -s "prefix(github.com/milvus-io)" --custom-order
@$(INSTALL_PATH)/gci write tests/ --skip-generated -s standard -s default -s "prefix(github.com/milvus-io)" --custom-order
@echo "Running golangci-lint auto-fix"
@source $(PWD)/scripts/setenv.sh && GO111MODULE=on $(INSTALL_PATH)/golangci-lint run --fix --timeout=30m --config $(PWD)/.golangci.yml;
@source $(PWD)/scripts/setenv.sh && cd pkg && GO111MODULE=on $(INSTALL_PATH)/golangci-lint run --fix --timeout=30m --config $(PWD)/.golangci.yml
@source $(PWD)/scripts/setenv.sh && cd client && GO111MODULE=on $(INSTALL_PATH)/golangci-lint run --fix --timeout=30m --config $(PWD)/client/.golangci.yml
#TODO: Check code specifications by golangci-lint
static-check: getdeps
@echo "Running $@ check"
@echo "Start check core packages"
@source $(PWD)/scripts/setenv.sh && GO111MODULE=on GOFLAGS=-buildvcs=false $(INSTALL_PATH)/golangci-lint run --build-tags dynamic,test --timeout=30m --config $(PWD)/.golangci.yml
@echo "Start check pkg package"
@source $(PWD)/scripts/setenv.sh && cd pkg && GO111MODULE=on GOFLAGS=-buildvcs=false $(INSTALL_PATH)/golangci-lint run --build-tags dynamic,test --timeout=30m --config $(PWD)/.golangci.yml
@echo "Start check client package"
@source $(PWD)/scripts/setenv.sh && cd client && GO111MODULE=on GOFLAGS=-buildvcs=false $(INSTALL_PATH)/golangci-lint run --timeout=30m --config $(PWD)/client/.golangci.yml
@echo "Start check go_client e2e package"
@source $(PWD)/scripts/setenv.sh && cd tests/go_client && GO111MODULE=on GOFLAGS=-buildvcs=false $(INSTALL_PATH)/golangci-lint run --build-tags L0,L1,L2,test --timeout=30m --config $(PWD)/tests/go_client/.golangci.yml
verifiers: build-cpp getdeps cppcheck fmt static-check
# Build various components locally.
binlog:
@echo "Building binlog ..."
@source $(PWD)/scripts/setenv.sh && \
mkdir -p $(INSTALL_PATH) && go env -w CGO_ENABLED="1" && \
Upgrade go from 1.20 to 1.21 (#33047) Signed-off-by: shaoting-huang [shaoting-huang@zilliz.com] issue: https://github.com/milvus-io/milvus/issues/32982 # Background Go 1.21 introduces several improvements and changes over Go 1.20, which is quite stable now. According to [Go 1.21 Release Notes](https://tip.golang.org/doc/go1.21), the big difference of Go 1.21 is enabling Profile-Guided Optimization by default, which can improve performance by around 2-14%. Here are the summary steps of PGO: 1. Build Initial Binary (Without PGO) 2. Deploying the Production Environment 3. Run the program and collect Performance Analysis Data (CPU pprof) 4. Analyze the Collected Data and Select a Performance Profile for PGO 5. Place the Performance Analysis File in the Main Package Directory and Name It default.pgo 6. go build Detects the default.pgo File and Enables PGO 7. Build and Release the Updated Binary (With PGO) 8. Iterate and Repeat the Above Steps <img width="657" alt="Screenshot 2024-05-14 at 15 57 01" src="https://github.com/milvus-io/milvus/assets/167743503/b08d4300-0be1-44dc-801f-ce681dabc581"> # What does this PR do There are three experiments, search benchmark by Zilliz test platform, search benchmark by open-source [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file), and search benchmark with PGO. We do both search benchmarks by Zilliz test platform and by VectorDBBench to reduce reliance on a single experimental result. Besides, we validate the performance enhancement with PGO. ## Search Benchmark Report by Zilliz Test Platform An upgrade to Go 1.21 was conducted on a Milvus Standalone server, equipped with 16 CPUs and 64GB of memory. The search performance was evaluated using a 1 million entry local dataset with an L2 metric type in a 768-dimensional space. The system was tested for concurrent searches with 50 concurrent tasks for 1 hour, each with a 20-second interval. The reason for using one server rather than two servers to compare is to guarantee the same data source and same segment state after compaction. Test Sequence: 1. Go 1.20 Initial Run: Insert data, build index, load index, and search. 2. Go 1.20 Rebuild: Rebuild the index with the same dataset, load index, and search. 3. Go 1.21 Load: Upload to Go 1.21 within the server. Then load the index from the second run, and search. 4. Go 1.21 Rebuild: Rebuild the index with the same dataset, load index, and search. Search Metrics: | Metric | Go 1.20 | Go 1.20 Rebuild Index | Go 1.21 | Go 1.21 Rebuild Index | |----------------------------|------------------|-----------------|------------------|-----------------| | `search requests` | 10,942,683 | 16,131,726 | 16,200,887 | 16,331,052 | | `search fails` | 0 | 0 | 0 | 0 | | `search RT_avg` (ms) | 16.44 | 11.15 | 11.11 | 11.02 | | `search RT_min` (ms) | 1.30 | 1.28 | 1.31 | 1.26 | | `search RT_max` (ms) | 446.61 | 233.22 | 235.90 | 147.93 | | `search TP50` (ms) | 11.74 | 10.46 | 10.43 | 10.35 | | `search TP99` (ms) | 92.30 | 25.76 | 25.36 | 25.23 | | `search RPS` | 3,039 | 4,481 | 4,500 | 4,536 | ### Key Findings The benchmark tests reveal that the index build time with Go 1.20 at 340.39 ms and Go 1.21 at 337.60 ms demonstrated negligible performance variance in index construction. However, Go 1.21 offers slightly better performance in search operations compared to Go 1.20, with improvements in handling concurrent tasks and reducing response times. ## Search Benchmark Report By VectorDb Bench Follow [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file) to create a VectorDb Bench test for Go 1.20 and Go 1.21. We test the search performance with Go 1.20 and Go 1.21 (without PGO) on the Milvus Standalone system. The tests were conducted using the Cohere dataset with 1 million entries in a 768-dimensional space, utilizing the COSINE metric type. Search Metrics: Metric | Go 1.20 | Go 1.21 without PGO -- | -- | -- Load Duration (seconds) | 1195.95 | 976.37 Queries Per Second (QPS) | 841.62 | 875.89 99th Percentile Serial Latency (seconds) | 0.0047 | 0.0076 Recall | 0.9487 | 0.9489 ### Key Findings Go 1.21 indicates faster index loading times and larger search QPS handling. ## PGO Performance Test Milvus has already added [net/http/pprof](https://pkg.go.dev/net/http/pprof) in the metrics. So we can curl the CPU profile directly by running `curl -o default.pgo "http://${MILVUS_SERVER_IP}:${MILVUS_SERVER_PORT}/debug/pprof/profile?seconds=${TIME_SECOND}"` to collect the profile as the default.pgo during the first search. Then I build Milvus with PGO and use the same index to run the search again. The result is as below: Search Metrics | Metric | Go 1.21 Without PGO | Go 1.21 With PGO | Change (%) | |---------------------------------------------|------------------|-----------------|------------| | `search Requests` | 2,644,583 | 2,837,726 | +7.30% | | `search Fails` | 0 | 0 | N/A | | `search RT_avg` (ms) | 11.34 | 10.57 | -6.78% | | `search RT_min` (ms) | 1.39 | 1.32 | -5.18% | | `search RT_max` (ms) | 349.72 | 143.72 | -58.91% | | `search TP50` (ms) | 10.57 | 9.93 | -6.05% | | `search TP99` (ms) | 26.14 | 24.16 | -7.56% | | `search RPS` | 4,407 | 4,729 | +7.30% | ### Key Findings PGO led to a notable enhancement in search performance, particularly in reducing the maximum response time by 58% and increasing the search QPS by 7.3%. ### Further Analysis Generate a diff flame graphs between two CPU profiles by running `go tool pprof -http=:8000 -diff_base nopgo.pgo pgo.pgo -normalize` <img width="1894" alt="goprofiling" src="https://github.com/milvus-io/milvus/assets/167743503/ab9e91eb-95c7-4963-acd9-d1c3c73ee010"> Further insight of HnswIndexNode and Milvus Search Handler <img width="1906" alt="hnsw" src="https://github.com/milvus-io/milvus/assets/167743503/a04cf4a0-7c97-4451-b3cf-98afc20a0b05"> <img width="1873" alt="search_handler" src="https://github.com/milvus-io/milvus/assets/167743503/5f4d3982-18dd-4115-8e76-460f7f534c7f"> After applying PGO to the Milvus server, the CPU utilization of the faiss::fvec_L2 function has decreased. This optimization significantly enhances the performance of the [HnswIndexNode::Search::searchKnn](https://github.com/zilliztech/knowhere/blob/e0c9c41aa22d8f6e6761a0a54460e4573de15bfe/src/index/hnsw/hnsw.cc#L203) method, which is frequently invoked by Knowhere during high-concurrency searches. As the explanation from Go release notes, the function might be more aggressively inlined by Go compiler during the second build with the CPU profiling collected from the first run. As a result, the search handler efficiency within Milvus DataNode has improved, allowing the server to process a higher number of search queries per second (QPS). # Conclusion The combination of Go 1.21 and PGO has led to substantial enhancements in search performance for Milvus server, particularly in terms of search QPS and response times, making it more efficient for handling high-concurrency search operations. Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
2024-05-22 13:21:39 +08:00
GO111MODULE=on $(GO) build -pgo=$(PGO_PATH)/default.pgo -ldflags="-r $${RPATH}" -o $(INSTALL_PATH)/binlog $(PWD)/cmd/tools/binlog/main.go 1>/dev/null
MIGRATION_PATH = $(PWD)/cmd/tools/migration
meta-migration:
@echo "Building migration tool ..."
@source $(PWD)/scripts/setenv.sh && \
mkdir -p $(INSTALL_PATH) && go env -w CGO_ENABLED="1" && \
Upgrade go from 1.20 to 1.21 (#33047) Signed-off-by: shaoting-huang [shaoting-huang@zilliz.com] issue: https://github.com/milvus-io/milvus/issues/32982 # Background Go 1.21 introduces several improvements and changes over Go 1.20, which is quite stable now. According to [Go 1.21 Release Notes](https://tip.golang.org/doc/go1.21), the big difference of Go 1.21 is enabling Profile-Guided Optimization by default, which can improve performance by around 2-14%. Here are the summary steps of PGO: 1. Build Initial Binary (Without PGO) 2. Deploying the Production Environment 3. Run the program and collect Performance Analysis Data (CPU pprof) 4. Analyze the Collected Data and Select a Performance Profile for PGO 5. Place the Performance Analysis File in the Main Package Directory and Name It default.pgo 6. go build Detects the default.pgo File and Enables PGO 7. Build and Release the Updated Binary (With PGO) 8. Iterate and Repeat the Above Steps <img width="657" alt="Screenshot 2024-05-14 at 15 57 01" src="https://github.com/milvus-io/milvus/assets/167743503/b08d4300-0be1-44dc-801f-ce681dabc581"> # What does this PR do There are three experiments, search benchmark by Zilliz test platform, search benchmark by open-source [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file), and search benchmark with PGO. We do both search benchmarks by Zilliz test platform and by VectorDBBench to reduce reliance on a single experimental result. Besides, we validate the performance enhancement with PGO. ## Search Benchmark Report by Zilliz Test Platform An upgrade to Go 1.21 was conducted on a Milvus Standalone server, equipped with 16 CPUs and 64GB of memory. The search performance was evaluated using a 1 million entry local dataset with an L2 metric type in a 768-dimensional space. The system was tested for concurrent searches with 50 concurrent tasks for 1 hour, each with a 20-second interval. The reason for using one server rather than two servers to compare is to guarantee the same data source and same segment state after compaction. Test Sequence: 1. Go 1.20 Initial Run: Insert data, build index, load index, and search. 2. Go 1.20 Rebuild: Rebuild the index with the same dataset, load index, and search. 3. Go 1.21 Load: Upload to Go 1.21 within the server. Then load the index from the second run, and search. 4. Go 1.21 Rebuild: Rebuild the index with the same dataset, load index, and search. Search Metrics: | Metric | Go 1.20 | Go 1.20 Rebuild Index | Go 1.21 | Go 1.21 Rebuild Index | |----------------------------|------------------|-----------------|------------------|-----------------| | `search requests` | 10,942,683 | 16,131,726 | 16,200,887 | 16,331,052 | | `search fails` | 0 | 0 | 0 | 0 | | `search RT_avg` (ms) | 16.44 | 11.15 | 11.11 | 11.02 | | `search RT_min` (ms) | 1.30 | 1.28 | 1.31 | 1.26 | | `search RT_max` (ms) | 446.61 | 233.22 | 235.90 | 147.93 | | `search TP50` (ms) | 11.74 | 10.46 | 10.43 | 10.35 | | `search TP99` (ms) | 92.30 | 25.76 | 25.36 | 25.23 | | `search RPS` | 3,039 | 4,481 | 4,500 | 4,536 | ### Key Findings The benchmark tests reveal that the index build time with Go 1.20 at 340.39 ms and Go 1.21 at 337.60 ms demonstrated negligible performance variance in index construction. However, Go 1.21 offers slightly better performance in search operations compared to Go 1.20, with improvements in handling concurrent tasks and reducing response times. ## Search Benchmark Report By VectorDb Bench Follow [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file) to create a VectorDb Bench test for Go 1.20 and Go 1.21. We test the search performance with Go 1.20 and Go 1.21 (without PGO) on the Milvus Standalone system. The tests were conducted using the Cohere dataset with 1 million entries in a 768-dimensional space, utilizing the COSINE metric type. Search Metrics: Metric | Go 1.20 | Go 1.21 without PGO -- | -- | -- Load Duration (seconds) | 1195.95 | 976.37 Queries Per Second (QPS) | 841.62 | 875.89 99th Percentile Serial Latency (seconds) | 0.0047 | 0.0076 Recall | 0.9487 | 0.9489 ### Key Findings Go 1.21 indicates faster index loading times and larger search QPS handling. ## PGO Performance Test Milvus has already added [net/http/pprof](https://pkg.go.dev/net/http/pprof) in the metrics. So we can curl the CPU profile directly by running `curl -o default.pgo "http://${MILVUS_SERVER_IP}:${MILVUS_SERVER_PORT}/debug/pprof/profile?seconds=${TIME_SECOND}"` to collect the profile as the default.pgo during the first search. Then I build Milvus with PGO and use the same index to run the search again. The result is as below: Search Metrics | Metric | Go 1.21 Without PGO | Go 1.21 With PGO | Change (%) | |---------------------------------------------|------------------|-----------------|------------| | `search Requests` | 2,644,583 | 2,837,726 | +7.30% | | `search Fails` | 0 | 0 | N/A | | `search RT_avg` (ms) | 11.34 | 10.57 | -6.78% | | `search RT_min` (ms) | 1.39 | 1.32 | -5.18% | | `search RT_max` (ms) | 349.72 | 143.72 | -58.91% | | `search TP50` (ms) | 10.57 | 9.93 | -6.05% | | `search TP99` (ms) | 26.14 | 24.16 | -7.56% | | `search RPS` | 4,407 | 4,729 | +7.30% | ### Key Findings PGO led to a notable enhancement in search performance, particularly in reducing the maximum response time by 58% and increasing the search QPS by 7.3%. ### Further Analysis Generate a diff flame graphs between two CPU profiles by running `go tool pprof -http=:8000 -diff_base nopgo.pgo pgo.pgo -normalize` <img width="1894" alt="goprofiling" src="https://github.com/milvus-io/milvus/assets/167743503/ab9e91eb-95c7-4963-acd9-d1c3c73ee010"> Further insight of HnswIndexNode and Milvus Search Handler <img width="1906" alt="hnsw" src="https://github.com/milvus-io/milvus/assets/167743503/a04cf4a0-7c97-4451-b3cf-98afc20a0b05"> <img width="1873" alt="search_handler" src="https://github.com/milvus-io/milvus/assets/167743503/5f4d3982-18dd-4115-8e76-460f7f534c7f"> After applying PGO to the Milvus server, the CPU utilization of the faiss::fvec_L2 function has decreased. This optimization significantly enhances the performance of the [HnswIndexNode::Search::searchKnn](https://github.com/zilliztech/knowhere/blob/e0c9c41aa22d8f6e6761a0a54460e4573de15bfe/src/index/hnsw/hnsw.cc#L203) method, which is frequently invoked by Knowhere during high-concurrency searches. As the explanation from Go release notes, the function might be more aggressively inlined by Go compiler during the second build with the CPU profiling collected from the first run. As a result, the search handler efficiency within Milvus DataNode has improved, allowing the server to process a higher number of search queries per second (QPS). # Conclusion The combination of Go 1.21 and PGO has led to substantial enhancements in search performance for Milvus server, particularly in terms of search QPS and response times, making it more efficient for handling high-concurrency search operations. Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
2024-05-22 13:21:39 +08:00
GO111MODULE=on $(GO) build -pgo=$(PGO_PATH)/default.pgo -ldflags="-r $${RPATH} -X '$(OBJPREFIX).BuildTags=$(BUILD_TAGS)' -X '$(OBJPREFIX).BuildTime=$(BUILD_TIME)' -X '$(OBJPREFIX).GitCommit=$(GIT_COMMIT)' -X '$(OBJPREFIX).GoVersion=$(GO_VERSION)'" \
-tags dynamic -o $(INSTALL_PATH)/meta-migration $(MIGRATION_PATH)/main.go 1>/dev/null
INTERATION_PATH = $(PWD)/tests/integration
integration-test: getdeps
@echo "Building integration tests ..."
@(env bash $(PWD)/scripts/run_intergration_test.sh "$(INSTALL_PATH)/gotestsum --")
BUILD_TAGS = $(shell git describe --tags --always --dirty="-dev")
BUILD_TAGS_GPU = ${BUILD_TAGS}-gpu
BUILD_TIME = $(shell date -u)
GIT_COMMIT = $(shell git rev-parse --short HEAD)
GO_VERSION = $(shell go version)
print-build-info:
$(shell git config --global --add safe.directory '*')
@echo "Build Tag: $(BUILD_TAGS)"
@echo "Build Time: $(BUILD_TIME)"
@echo "Git Commit: $(GIT_COMMIT)"
@echo "Go Version: $(GO_VERSION)"
print-gpu-build-info:
$(shell git config --global --add safe.directory '*')
@echo "Build Tag: $(BUILD_TAGS_GPU)"
@echo "Build Time: $(BUILD_TIME)"
@echo "Git Commit: $(GIT_COMMIT)"
@echo "Go Version: $(GO_VERSION)"
update-milvus-api: download-milvus-proto
@echo "Update milvus/api version ..."
@(env bash $(PWD)/scripts/update-api-version.sh $(PROTO_API_VERSION))
download-milvus-proto:
@echo "Download milvus-proto repo ..."
@(env bash $(PWD)/scripts/download_milvus_proto.sh)
build-3rdparty:
@echo "Build 3rdparty ..."
@(env bash $(PWD)/scripts/3rdparty_build.sh -o ${use_opendal})
generated-proto-without-cpp: download-milvus-proto get-proto-deps
@echo "Generate proto ..."
@(env bash $(PWD)/scripts/generate_proto.sh ${INSTALL_PATH})
generated-proto: download-milvus-proto build-3rdparty get-proto-deps
@echo "Generate proto ..."
@(env bash $(PWD)/scripts/generate_proto.sh ${INSTALL_PATH})
build-cpp: generated-proto
@echo "Building Milvus cpp library ..."
@(env bash $(PWD)/scripts/core_build.sh -t ${mode} -a ${use_asan} -n ${use_disk_index} -y ${use_dynamic_simd} ${AZURE_OPTION} -x ${index_engine} -o ${use_opendal})
build-cpp-gpu: generated-proto
@echo "Building Milvus cpp gpu library ... "
@(env bash $(PWD)/scripts/core_build.sh -t ${mode} -g -n ${use_disk_index} -y ${use_dynamic_simd} ${AZURE_OPTION} -x ${index_engine} -o ${use_opendal})
build-cpp-with-unittest: generated-proto
@echo "Building Milvus cpp library with unittest ... "
@(env bash $(PWD)/scripts/core_build.sh -t ${mode} -u -n ${use_disk_index} -y ${use_dynamic_simd} ${AZURE_OPTION} -x ${index_engine} -o ${use_opendal})
build-cpp-with-coverage: generated-proto
@echo "Building Milvus cpp library with coverage and unittest ..."
@(env bash $(PWD)/scripts/core_build.sh -t ${mode} -a ${use_asan} -u -c -n ${use_disk_index} -y ${use_dynamic_simd} ${AZURE_OPTION} -x ${index_engine} -o ${use_opendal})
check-proto-product: generated-proto
@(env bash $(PWD)/scripts/check_proto_product.sh)
# Run the tests.
unittest: test-cpp test-go
test-util:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t util)
test-storage:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t storage)
test-allocator:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t allocator)
test-config:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t config)
test-tso:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t tso)
test-kv:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t kv)
test-mq:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t mq)
test-rootcoord:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t rootcoord)
test-indexnode:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t indexnode)
test-indexcoord:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t indexcoord)
test-proxy:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t proxy)
test-datacoord:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t datacoord)
test-datanode:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t datanode)
test-querynode:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t querynode)
test-querycoord:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t querycoord)
test-metastore:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t metastore)
test-streaming:
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh -t streaming)
test-go: build-cpp-with-unittest
@echo "Running go unittests..."
@(env bash $(PWD)/scripts/run_go_unittest.sh)
test-cpp: build-cpp-with-unittest
@echo "Running cpp unittests..."
@(env bash $(PWD)/scripts/run_cpp_unittest.sh)
run-test-cpp:
@echo "Running cpp unittests..."
@echo $(PWD)/scripts/run_cpp_unittest.sh arg=${filter}
@(env bash $(PWD)/scripts/run_cpp_unittest.sh arg=${filter})
# Run code coverage.
codecov: codecov-go codecov-cpp
# Run codecov-go
codecov-go: build-cpp-with-coverage
@echo "Running go coverage..."
@(env bash $(PWD)/scripts/run_go_codecov.sh)
# Run codecov-go without build core again, used in github action
codecov-go-without-build: getdeps
@echo "Running go coverage..."
@(env bash $(PWD)/scripts/run_go_codecov.sh "$(INSTALL_PATH)/gotestsum --")
# Run codecov-cpp
codecov-cpp: build-cpp-with-coverage
@echo "Running cpp coverage..."
@(env bash $(PWD)/scripts/run_cpp_codecov.sh)
# Build each component and install binary to $GOPATH/bin.
install: milvus
@echo "Installing binary to './bin'"
@(env GOPATH=$(GOPATH) LIBRARY_PATH=$(LIBRARY_PATH) bash $(PWD)/scripts/install_milvus.sh)
@echo "Installation successful."
gpu-install: milvus-gpu
@echo "Installing binary to './bin'"
@(env GOPATH=$(GOPATH) LIBRARY_PATH=$(LIBRARY_PATH) bash $(PWD)/scripts/install_milvus.sh)
@echo "Installation successful."
clean:
@echo "Cleaning up all the generated files"
@rm -rf bin/
@rm -rf lib/
@rm -rf $(GOPATH)/bin/milvus
@rm -rf cmake_build
@rm -rf internal/core/output
milvus-tools: print-build-info
@echo "Building tools ..."
@. $(PWD)/scripts/setenv.sh && mkdir -p $(INSTALL_PATH)/tools && go env -w CGO_ENABLED="1" && GO111MODULE=on $(GO) build \
Upgrade go from 1.20 to 1.21 (#33047) Signed-off-by: shaoting-huang [shaoting-huang@zilliz.com] issue: https://github.com/milvus-io/milvus/issues/32982 # Background Go 1.21 introduces several improvements and changes over Go 1.20, which is quite stable now. According to [Go 1.21 Release Notes](https://tip.golang.org/doc/go1.21), the big difference of Go 1.21 is enabling Profile-Guided Optimization by default, which can improve performance by around 2-14%. Here are the summary steps of PGO: 1. Build Initial Binary (Without PGO) 2. Deploying the Production Environment 3. Run the program and collect Performance Analysis Data (CPU pprof) 4. Analyze the Collected Data and Select a Performance Profile for PGO 5. Place the Performance Analysis File in the Main Package Directory and Name It default.pgo 6. go build Detects the default.pgo File and Enables PGO 7. Build and Release the Updated Binary (With PGO) 8. Iterate and Repeat the Above Steps <img width="657" alt="Screenshot 2024-05-14 at 15 57 01" src="https://github.com/milvus-io/milvus/assets/167743503/b08d4300-0be1-44dc-801f-ce681dabc581"> # What does this PR do There are three experiments, search benchmark by Zilliz test platform, search benchmark by open-source [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file), and search benchmark with PGO. We do both search benchmarks by Zilliz test platform and by VectorDBBench to reduce reliance on a single experimental result. Besides, we validate the performance enhancement with PGO. ## Search Benchmark Report by Zilliz Test Platform An upgrade to Go 1.21 was conducted on a Milvus Standalone server, equipped with 16 CPUs and 64GB of memory. The search performance was evaluated using a 1 million entry local dataset with an L2 metric type in a 768-dimensional space. The system was tested for concurrent searches with 50 concurrent tasks for 1 hour, each with a 20-second interval. The reason for using one server rather than two servers to compare is to guarantee the same data source and same segment state after compaction. Test Sequence: 1. Go 1.20 Initial Run: Insert data, build index, load index, and search. 2. Go 1.20 Rebuild: Rebuild the index with the same dataset, load index, and search. 3. Go 1.21 Load: Upload to Go 1.21 within the server. Then load the index from the second run, and search. 4. Go 1.21 Rebuild: Rebuild the index with the same dataset, load index, and search. Search Metrics: | Metric | Go 1.20 | Go 1.20 Rebuild Index | Go 1.21 | Go 1.21 Rebuild Index | |----------------------------|------------------|-----------------|------------------|-----------------| | `search requests` | 10,942,683 | 16,131,726 | 16,200,887 | 16,331,052 | | `search fails` | 0 | 0 | 0 | 0 | | `search RT_avg` (ms) | 16.44 | 11.15 | 11.11 | 11.02 | | `search RT_min` (ms) | 1.30 | 1.28 | 1.31 | 1.26 | | `search RT_max` (ms) | 446.61 | 233.22 | 235.90 | 147.93 | | `search TP50` (ms) | 11.74 | 10.46 | 10.43 | 10.35 | | `search TP99` (ms) | 92.30 | 25.76 | 25.36 | 25.23 | | `search RPS` | 3,039 | 4,481 | 4,500 | 4,536 | ### Key Findings The benchmark tests reveal that the index build time with Go 1.20 at 340.39 ms and Go 1.21 at 337.60 ms demonstrated negligible performance variance in index construction. However, Go 1.21 offers slightly better performance in search operations compared to Go 1.20, with improvements in handling concurrent tasks and reducing response times. ## Search Benchmark Report By VectorDb Bench Follow [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file) to create a VectorDb Bench test for Go 1.20 and Go 1.21. We test the search performance with Go 1.20 and Go 1.21 (without PGO) on the Milvus Standalone system. The tests were conducted using the Cohere dataset with 1 million entries in a 768-dimensional space, utilizing the COSINE metric type. Search Metrics: Metric | Go 1.20 | Go 1.21 without PGO -- | -- | -- Load Duration (seconds) | 1195.95 | 976.37 Queries Per Second (QPS) | 841.62 | 875.89 99th Percentile Serial Latency (seconds) | 0.0047 | 0.0076 Recall | 0.9487 | 0.9489 ### Key Findings Go 1.21 indicates faster index loading times and larger search QPS handling. ## PGO Performance Test Milvus has already added [net/http/pprof](https://pkg.go.dev/net/http/pprof) in the metrics. So we can curl the CPU profile directly by running `curl -o default.pgo "http://${MILVUS_SERVER_IP}:${MILVUS_SERVER_PORT}/debug/pprof/profile?seconds=${TIME_SECOND}"` to collect the profile as the default.pgo during the first search. Then I build Milvus with PGO and use the same index to run the search again. The result is as below: Search Metrics | Metric | Go 1.21 Without PGO | Go 1.21 With PGO | Change (%) | |---------------------------------------------|------------------|-----------------|------------| | `search Requests` | 2,644,583 | 2,837,726 | +7.30% | | `search Fails` | 0 | 0 | N/A | | `search RT_avg` (ms) | 11.34 | 10.57 | -6.78% | | `search RT_min` (ms) | 1.39 | 1.32 | -5.18% | | `search RT_max` (ms) | 349.72 | 143.72 | -58.91% | | `search TP50` (ms) | 10.57 | 9.93 | -6.05% | | `search TP99` (ms) | 26.14 | 24.16 | -7.56% | | `search RPS` | 4,407 | 4,729 | +7.30% | ### Key Findings PGO led to a notable enhancement in search performance, particularly in reducing the maximum response time by 58% and increasing the search QPS by 7.3%. ### Further Analysis Generate a diff flame graphs between two CPU profiles by running `go tool pprof -http=:8000 -diff_base nopgo.pgo pgo.pgo -normalize` <img width="1894" alt="goprofiling" src="https://github.com/milvus-io/milvus/assets/167743503/ab9e91eb-95c7-4963-acd9-d1c3c73ee010"> Further insight of HnswIndexNode and Milvus Search Handler <img width="1906" alt="hnsw" src="https://github.com/milvus-io/milvus/assets/167743503/a04cf4a0-7c97-4451-b3cf-98afc20a0b05"> <img width="1873" alt="search_handler" src="https://github.com/milvus-io/milvus/assets/167743503/5f4d3982-18dd-4115-8e76-460f7f534c7f"> After applying PGO to the Milvus server, the CPU utilization of the faiss::fvec_L2 function has decreased. This optimization significantly enhances the performance of the [HnswIndexNode::Search::searchKnn](https://github.com/zilliztech/knowhere/blob/e0c9c41aa22d8f6e6761a0a54460e4573de15bfe/src/index/hnsw/hnsw.cc#L203) method, which is frequently invoked by Knowhere during high-concurrency searches. As the explanation from Go release notes, the function might be more aggressively inlined by Go compiler during the second build with the CPU profiling collected from the first run. As a result, the search handler efficiency within Milvus DataNode has improved, allowing the server to process a higher number of search queries per second (QPS). # Conclusion The combination of Go 1.21 and PGO has led to substantial enhancements in search performance for Milvus server, particularly in terms of search QPS and response times, making it more efficient for handling high-concurrency search operations. Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
2024-05-22 13:21:39 +08:00
-pgo=$(PGO_PATH)/default.pgo -ldflags="-X 'main.BuildTags=$(BUILD_TAGS)' -X 'main.BuildTime=$(BUILD_TIME)' -X 'main.GitCommit=$(GIT_COMMIT)' -X 'main.GoVersion=$(GO_VERSION)'" \
-o $(INSTALL_PATH)/tools $(PWD)/cmd/tools/* 1>/dev/null
rpm-setup:
@echo "Setuping rpm env ...;"
@build/rpm/setup-env.sh
rpm: install
@echo "Note: run 'make rpm-setup' to setup build env for rpm builder"
@echo "Building rpm ...;"
@yum -y install rpm-build rpmdevtools wget
@rm -rf ~/rpmbuild/BUILD/*
@rpmdev-setuptree
@wget https://github.com/etcd-io/etcd/releases/download/v3.5.0/etcd-v3.5.0-linux-amd64.tar.gz && tar -xf etcd-v3.5.0-linux-amd64.tar.gz
@cp etcd-v3.5.0-linux-amd64/etcd bin/etcd
@wget https://dl.min.io/server/minio/release/linux-amd64/archive/minio.RELEASE.2021-02-14T04-01-33Z -O bin/minio
@cp -r bin ~/rpmbuild/BUILD/
@cp -r lib ~/rpmbuild/BUILD/
@cp -r configs ~/rpmbuild/BUILD/
@cp -r build/rpm/services ~/rpmbuild/BUILD/
@QA_RPATHS="$$[ 0x001|0x0002|0x0020 ]" rpmbuild -ba ./build/rpm/milvus.spec
generate-mockery-types: getdeps
# RootCoord
$(INSTALL_PATH)/mockery --name=RootCoordComponent --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_rootcoord.go --with-expecter --structname=RootCoord
# Proxy
$(INSTALL_PATH)/mockery --name=ProxyComponent --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_proxy.go --with-expecter --structname=MockProxy
# QueryCoord
$(INSTALL_PATH)/mockery --name=QueryCoordComponent --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_querycoord.go --with-expecter --structname=MockQueryCoord
# QueryNode
$(INSTALL_PATH)/mockery --name=QueryNodeComponent --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_querynode.go --with-expecter --structname=MockQueryNode
# DataCoord
$(INSTALL_PATH)/mockery --name=DataCoordComponent --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_datacoord.go --with-expecter --structname=MockDataCoord
# DataNode
$(INSTALL_PATH)/mockery --name=DataNodeComponent --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_datanode.go --with-expecter --structname=MockDataNode
# IndexNode
$(INSTALL_PATH)/mockery --name=IndexNodeComponent --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_indexnode.go --with-expecter --structname=MockIndexNode
# Clients
$(INSTALL_PATH)/mockery --name=RootCoordClient --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_rootcoord_client.go --with-expecter --structname=MockRootCoordClient
$(INSTALL_PATH)/mockery --name=QueryCoordClient --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_querycoord_client.go --with-expecter --structname=MockQueryCoordClient
$(INSTALL_PATH)/mockery --name=DataCoordClient --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_datacoord_client.go --with-expecter --structname=MockDataCoordClient
$(INSTALL_PATH)/mockery --name=QueryNodeClient --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_querynode_client.go --with-expecter --structname=MockQueryNodeClient
$(INSTALL_PATH)/mockery --name=DataNodeClient --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_datanode_client.go --with-expecter --structname=MockDataNodeClient
$(INSTALL_PATH)/mockery --name=IndexNodeClient --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_indexnode_client.go --with-expecter --structname=MockIndexNodeClient
$(INSTALL_PATH)/mockery --name=ProxyClient --dir=$(PWD)/internal/types --output=$(PWD)/internal/mocks --filename=mock_proxy_client.go --with-expecter --structname=MockProxyClient
generate-mockery-rootcoord: getdeps
$(INSTALL_PATH)/mockery --name=IMetaTable --dir=$(PWD)/internal/rootcoord --output=$(PWD)/internal/rootcoord/mocks --filename=meta_table.go --with-expecter --outpkg=mockrootcoord
$(INSTALL_PATH)/mockery --name=GarbageCollector --dir=$(PWD)/internal/rootcoord --output=$(PWD)/internal/rootcoord/mocks --filename=garbage_collector.go --with-expecter --outpkg=mockrootcoord
generate-mockery-proxy: getdeps
$(INSTALL_PATH)/mockery --name=Cache --dir=$(PWD)/internal/proxy --output=$(PWD)/internal/proxy --filename=mock_cache.go --structname=MockCache --with-expecter --outpkg=proxy --inpackage
$(INSTALL_PATH)/mockery --name=timestampAllocatorInterface --dir=$(PWD)/internal/proxy --output=$(PWD)/internal/proxy --filename=mock_tso_test.go --structname=mockTimestampAllocator --with-expecter --outpkg=proxy --inpackage
$(INSTALL_PATH)/mockery --name=LBPolicy --dir=$(PWD)/internal/proxy --output=$(PWD)/internal/proxy --filename=mock_lb_policy.go --structname=MockLBPolicy --with-expecter --outpkg=proxy --inpackage
$(INSTALL_PATH)/mockery --name=LBBalancer --dir=$(PWD)/internal/proxy --output=$(PWD)/internal/proxy --filename=mock_lb_balancer.go --structname=MockLBBalancer --with-expecter --outpkg=proxy --inpackage
$(INSTALL_PATH)/mockery --name=shardClientMgr --dir=$(PWD)/internal/proxy --output=$(PWD)/internal/proxy --filename=mock_shardclient_manager.go --structname=MockShardClientManager --with-expecter --outpkg=proxy --inpackage
$(INSTALL_PATH)/mockery --name=channelsMgr --dir=$(PWD)/internal/proxy --output=$(PWD)/internal/proxy --filename=mock_channels_manager.go --structname=MockChannelsMgr --with-expecter --outpkg=proxy --inpackage
generate-mockery-querycoord: getdeps
$(INSTALL_PATH)/mockery --name=QueryNodeServer --dir=$(PWD)/internal/proto/querypb/ --output=$(PWD)/internal/querycoordv2/mocks --filename=mock_querynode.go --with-expecter --structname=MockQueryNodeServer
$(INSTALL_PATH)/mockery --name=Broker --dir=$(PWD)/internal/querycoordv2/meta --output=$(PWD)/internal/querycoordv2/meta --filename=mock_broker.go --with-expecter --structname=MockBroker --outpkg=meta
$(INSTALL_PATH)/mockery --name=TargetManagerInterface --dir=$(PWD)/internal/querycoordv2/meta --output=$(PWD)/internal/querycoordv2/meta --filename=mock_target_manager.go --with-expecter --structname=MockTargetManager --inpackage
$(INSTALL_PATH)/mockery --name=Scheduler --dir=$(PWD)/internal/querycoordv2/task --output=$(PWD)/internal/querycoordv2/task --filename=mock_scheduler.go --with-expecter --structname=MockScheduler --outpkg=task --inpackage
$(INSTALL_PATH)/mockery --name=Cluster --dir=$(PWD)/internal/querycoordv2/session --output=$(PWD)/internal/querycoordv2/session --filename=mock_cluster.go --with-expecter --structname=MockCluster --outpkg=session --inpackage
$(INSTALL_PATH)/mockery --name=Balance --dir=$(PWD)/internal/querycoordv2/balance --output=$(PWD)/internal/querycoordv2/balance --filename=mock_balancer.go --with-expecter --structname=MockBalancer --outpkg=balance --inpackage
$(INSTALL_PATH)/mockery --name=Controller --dir=$(PWD)/internal/querycoordv2/dist --output=$(PWD)/internal/querycoordv2/dist --filename=mock_controller.go --with-expecter --structname=MockController --outpkg=dist --inpackage
generate-mockery-querynode: getdeps build-cpp
@source $(PWD)/scripts/setenv.sh # setup PKG_CONFIG_PATH
$(INSTALL_PATH)/mockery --name=QueryHook --dir=$(PWD)/internal/querynodev2/optimizers --output=$(PWD)/internal/querynodev2/optimizers --filename=mock_query_hook.go --with-expecter --outpkg=optimizers --structname=MockQueryHook --inpackage
$(INSTALL_PATH)/mockery --name=Manager --dir=$(PWD)/internal/querynodev2/cluster --output=$(PWD)/internal/querynodev2/cluster --filename=mock_manager.go --with-expecter --outpkg=cluster --structname=MockManager --inpackage
$(INSTALL_PATH)/mockery --name=SegmentManager --dir=$(PWD)/internal/querynodev2/segments --output=$(PWD)/internal/querynodev2/segments --filename=mock_segment_manager.go --with-expecter --outpkg=segments --structname=MockSegmentManager --inpackage
$(INSTALL_PATH)/mockery --name=CollectionManager --dir=$(PWD)/internal/querynodev2/segments --output=$(PWD)/internal/querynodev2/segments --filename=mock_collection_manager.go --with-expecter --outpkg=segments --structname=MockCollectionManager --inpackage
$(INSTALL_PATH)/mockery --name=Loader --dir=$(PWD)/internal/querynodev2/segments --output=$(PWD)/internal/querynodev2/segments --filename=mock_loader.go --with-expecter --outpkg=segments --structname=MockLoader --inpackage
$(INSTALL_PATH)/mockery --name=Segment --dir=$(PWD)/internal/querynodev2/segments --output=$(PWD)/internal/querynodev2/segments --filename=mock_segment.go --with-expecter --outpkg=segments --structname=MockSegment --inpackage
$(INSTALL_PATH)/mockery --name=Worker --dir=$(PWD)/internal/querynodev2/cluster --output=$(PWD)/internal/querynodev2/cluster --filename=mock_worker.go --with-expecter --outpkg=worker --structname=MockWorker --inpackage
$(INSTALL_PATH)/mockery --name=ShardDelegator --dir=$(PWD)/internal/querynodev2/delegator/ --output=$(PWD)/internal/querynodev2/delegator/ --filename=mock_delegator.go --with-expecter --outpkg=delegator --structname=MockShardDelegator --inpackage
generate-mockery-datacoord: getdeps
$(INSTALL_PATH)/mockery --name=compactionPlanContext --dir=internal/datacoord --filename=mock_compaction_plan_context.go --output=internal/datacoord --structname=MockCompactionPlanContext --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=Handler --dir=internal/datacoord --filename=mock_handler.go --output=internal/datacoord --structname=NMockHandler --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=Allocator --dir=internal/datacoord/allocator --filename=mock_allocator.go --output=internal/datacoord/allocator --structname=MockAllocator --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=DataNodeManager --dir=internal/datacoord/session --filename=mock_datanode_manager.go --output=internal/datacoord/session --structname=MockDataNodeManager --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=RWChannelStore --dir=internal/datacoord --filename=mock_channel_store.go --output=internal/datacoord --structname=MockRWChannelStore --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=IndexEngineVersionManager --dir=internal/datacoord --filename=mock_index_engine_version_manager.go --output=internal/datacoord --structname=MockVersionManager --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=TriggerManager --dir=internal/datacoord --filename=mock_trigger_manager.go --output=internal/datacoord --structname=MockTriggerManager --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=Cluster --dir=internal/datacoord --filename=mock_cluster.go --output=internal/datacoord --structname=MockCluster --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=compactionPlanContext --dir=internal/datacoord --filename=mock_compaction_plan_context.go --output=internal/datacoord --structname=MockCompactionPlanContext --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=CompactionMeta --dir=internal/datacoord --filename=mock_compaction_meta.go --output=internal/datacoord --structname=MockCompactionMeta --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=ChannelManager --dir=internal/datacoord --filename=mock_channelmanager.go --output=internal/datacoord --structname=MockChannelManager --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=SubCluster --dir=internal/datacoord --filename=mock_subcluster.go --output=internal/datacoord --structname=MockSubCluster --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=Broker --dir=internal/datacoord/broker --filename=mock_coordinator_broker.go --output=internal/datacoord/broker --structname=MockBroker --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=WorkerManager --dir=internal/datacoord/session --filename=mock_worker_manager.go --output=internal/datacoord/session --structname=MockWorkerManager --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=Manager --dir=internal/datacoord --filename=mock_segment_manager.go --output=internal/datacoord --structname=MockManager --with-expecter --inpackage
$(INSTALL_PATH)/mockery --name=StatsJobManager --dir=internal/datacoord --filename=mock_job_manager.go --output=internal/datacoord --structname=MockStatsJobManager --with-expecter --inpackage
generate-mockery-datanode: getdeps
$(INSTALL_PATH)/mockery --name=Allocator --dir=$(PWD)/internal/datanode/allocator --output=$(PWD)/internal/datanode/allocator --filename=mock_allocator.go --with-expecter --structname=MockAllocator --outpkg=allocator --inpackage
$(INSTALL_PATH)/mockery --name=ChannelManager --dir=$(PWD)/internal/datanode/channel --output=$(PWD)/internal/datanode/channel --filename=mock_channelmanager.go --with-expecter --structname=MockChannelManager --outpkg=channel --inpackage
$(INSTALL_PATH)/mockery --name=Compactor --dir=$(PWD)/internal/datanode/compaction --output=$(PWD)/internal/datanode/compaction --filename=mock_compactor.go --with-expecter --structname=MockCompactor --outpkg=compaction --inpackage
generate-mockery-flushcommon: getdeps
$(INSTALL_PATH)/mockery --name=Broker --dir=$(PWD)/internal/flushcommon/broker --output=$(PWD)/internal/flushcommon/broker/ --filename=mock_broker.go --with-expecter --structname=MockBroker --outpkg=broker --inpackage
$(INSTALL_PATH)/mockery --name=MetaCache --dir=$(PWD)/internal/flushcommon/metacache --output=$(PWD)/internal/flushcommon/metacache --filename=mock_meta_cache.go --with-expecter --structname=MockMetaCache --outpkg=metacache --inpackage
$(INSTALL_PATH)/mockery --name=SyncManager --dir=$(PWD)/internal/flushcommon/syncmgr --output=$(PWD)/internal/flushcommon/syncmgr --filename=mock_sync_manager.go --with-expecter --structname=MockSyncManager --outpkg=syncmgr --inpackage
$(INSTALL_PATH)/mockery --name=MetaWriter --dir=$(PWD)/internal/flushcommon/syncmgr --output=$(PWD)/internal/flushcommon/syncmgr --filename=mock_meta_writer.go --with-expecter --structname=MockMetaWriter --outpkg=syncmgr --inpackage
$(INSTALL_PATH)/mockery --name=Serializer --dir=$(PWD)/internal/flushcommon/syncmgr --output=$(PWD)/internal/flushcommon/syncmgr --filename=mock_serializer.go --with-expecter --structname=MockSerializer --outpkg=syncmgr --inpackage
$(INSTALL_PATH)/mockery --name=Task --dir=$(PWD)/internal/flushcommon/syncmgr --output=$(PWD)/internal/flushcommon/syncmgr --filename=mock_task.go --with-expecter --structname=MockTask --outpkg=syncmgr --inpackage
$(INSTALL_PATH)/mockery --name=WriteBuffer --dir=$(PWD)/internal/flushcommon/writebuffer --output=$(PWD)/internal/flushcommon/writebuffer --filename=mock_write_buffer.go --with-expecter --structname=MockWriteBuffer --outpkg=writebuffer --inpackage
$(INSTALL_PATH)/mockery --name=BufferManager --dir=$(PWD)/internal/flushcommon/writebuffer --output=$(PWD)/internal/flushcommon/writebuffer --filename=mock_manager.go --with-expecter --structname=MockBufferManager --outpkg=writebuffer --inpackage
$(INSTALL_PATH)/mockery --name=BinlogIO --dir=$(PWD)/internal/flushcommon/io --output=$(PWD)/internal/flushcommon/io --filename=mock_binlogio.go --with-expecter --structname=MockBinlogIO --outpkg=io --inpackage
$(INSTALL_PATH)/mockery --name=FlowgraphManager --dir=$(PWD)/internal/flushcommon/pipeline --output=$(PWD)/internal/flushcommon/pipeline --filename=mock_fgmanager.go --with-expecter --structname=MockFlowgraphManager --outpkg=pipeline --inpackage
generate-mockery-metastore: getdeps
$(INSTALL_PATH)/mockery --name=RootCoordCatalog --dir=$(PWD)/internal/metastore --output=$(PWD)/internal/metastore/mocks --filename=mock_rootcoord_catalog.go --with-expecter --structname=RootCoordCatalog --outpkg=mocks
$(INSTALL_PATH)/mockery --name=DataCoordCatalog --dir=$(PWD)/internal/metastore --output=$(PWD)/internal/metastore/mocks --filename=mock_datacoord_catalog.go --with-expecter --structname=DataCoordCatalog --outpkg=mocks
$(INSTALL_PATH)/mockery --name=QueryCoordCatalog --dir=$(PWD)/internal/metastore --output=$(PWD)/internal/metastore/mocks --filename=mock_querycoord_catalog.go --with-expecter --structname=QueryCoordCatalog --outpkg=mocks
generate-mockery-utils: getdeps
# dependency.Factory
$(INSTALL_PATH)/mockery --name=Factory --dir=internal/util/dependency --output=internal/util/dependency --filename=mock_factory.go --with-expecter --structname=MockFactory --inpackage
# tso.Allocator
$(INSTALL_PATH)/mockery --name=Allocator --dir=internal/tso --output=internal/tso/mocks --filename=allocator.go --with-expecter --structname=Allocator --outpkg=mocktso
$(INSTALL_PATH)/mockery --name=SessionInterface --dir=$(PWD)/internal/util/sessionutil --output=$(PWD)/internal/util/sessionutil --filename=mock_session.go --with-expecter --structname=MockSession --inpackage
$(INSTALL_PATH)/mockery --name=GrpcClient --dir=$(PWD)/internal/util/grpcclient --output=$(PWD)/internal/mocks --filename=mock_grpc_client.go --with-expecter --structname=MockGrpcClient
# proxy_client_manager.go
$(INSTALL_PATH)/mockery --name=ProxyClientManagerInterface --dir=$(PWD)/internal/util/proxyutil --output=$(PWD)/internal/util/proxyutil --filename=mock_proxy_client_manager.go --with-expecter --structname=MockProxyClientManager --inpackage
$(INSTALL_PATH)/mockery --name=ProxyWatcherInterface --dir=$(PWD)/internal/util/proxyutil --output=$(PWD)/internal/util/proxyutil --filename=mock_proxy_watcher.go --with-expecter --structname=MockProxyWatcher --inpackage
# function
$(INSTALL_PATH)/mockery --name=FunctionRunner --dir=$(PWD)/internal/util/function --output=$(PWD)/internal/util/function --filename=mock_function.go --with-expecter --structname=MockFunctionRunner --inpackage
$(INSTALL_PATH)/mockery --name=GlobalIDAllocatorInterface --dir=internal/allocator --output=internal/allocator --filename=mock_global_id_allocator.go --with-expecter --structname=MockGlobalIDAllocator --inpackage
generate-mockery-kv: getdeps
$(INSTALL_PATH)/mockery --name=TxnKV --dir=$(PWD)/pkg/kv --output=$(PWD)/internal/kv/mocks --filename=txn_kv.go --with-expecter
$(INSTALL_PATH)/mockery --name=MetaKv --dir=$(PWD)/pkg/kv --output=$(PWD)/internal/kv/mocks --filename=meta_kv.go --with-expecter
$(INSTALL_PATH)/mockery --name=WatchKV --dir=$(PWD)/pkg/kv --output=$(PWD)/internal/kv/mocks --filename=watch_kv.go --with-expecter
$(INSTALL_PATH)/mockery --name=SnapShotKV --dir=$(PWD)/pkg/kv --output=$(PWD)/internal/kv/mocks --filename=snapshot_kv.go --with-expecter
$(INSTALL_PATH)/mockery --name=Predicate --dir=$(PWD)/pkg/kv/predicates --output=$(PWD)/internal/kv/predicates --filename=mock_predicate.go --with-expecter --inpackage
generate-mockery-chunk-manager: getdeps
$(INSTALL_PATH)/mockery --name=ChunkManager --dir=$(PWD)/internal/storage --output=$(PWD)/internal/mocks --filename=mock_chunk_manager.go --with-expecter
generate-mockery-pkg:
$(MAKE) -C pkg generate-mockery
generate-mockery-internal: getdeps
$(INSTALL_PATH)/mockery --config $(PWD)/internal/.mockery.yaml
generate-mockery: generate-mockery-types generate-mockery-kv generate-mockery-rootcoord generate-mockery-proxy generate-mockery-querycoord generate-mockery-querynode generate-mockery-datacoord generate-mockery-pkg generate-mockery-internal
generate-yaml: milvus-tools
@echo "Updating milvus config yaml"
@$(PWD)/bin/tools/config gen-yaml && mv milvus.yaml configs/milvus.yaml
MMAP_MIGRATION_PATH = $(PWD)/cmd/tools/migration/mmap/tool
mmap-migration:
@echo "Building migration tool ..."
@source $(PWD)/scripts/setenv.sh && \
mkdir -p $(INSTALL_PATH) && go env -w CGO_ENABLED="1" && \
Upgrade go from 1.20 to 1.21 (#33047) Signed-off-by: shaoting-huang [shaoting-huang@zilliz.com] issue: https://github.com/milvus-io/milvus/issues/32982 # Background Go 1.21 introduces several improvements and changes over Go 1.20, which is quite stable now. According to [Go 1.21 Release Notes](https://tip.golang.org/doc/go1.21), the big difference of Go 1.21 is enabling Profile-Guided Optimization by default, which can improve performance by around 2-14%. Here are the summary steps of PGO: 1. Build Initial Binary (Without PGO) 2. Deploying the Production Environment 3. Run the program and collect Performance Analysis Data (CPU pprof) 4. Analyze the Collected Data and Select a Performance Profile for PGO 5. Place the Performance Analysis File in the Main Package Directory and Name It default.pgo 6. go build Detects the default.pgo File and Enables PGO 7. Build and Release the Updated Binary (With PGO) 8. Iterate and Repeat the Above Steps <img width="657" alt="Screenshot 2024-05-14 at 15 57 01" src="https://github.com/milvus-io/milvus/assets/167743503/b08d4300-0be1-44dc-801f-ce681dabc581"> # What does this PR do There are three experiments, search benchmark by Zilliz test platform, search benchmark by open-source [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file), and search benchmark with PGO. We do both search benchmarks by Zilliz test platform and by VectorDBBench to reduce reliance on a single experimental result. Besides, we validate the performance enhancement with PGO. ## Search Benchmark Report by Zilliz Test Platform An upgrade to Go 1.21 was conducted on a Milvus Standalone server, equipped with 16 CPUs and 64GB of memory. The search performance was evaluated using a 1 million entry local dataset with an L2 metric type in a 768-dimensional space. The system was tested for concurrent searches with 50 concurrent tasks for 1 hour, each with a 20-second interval. The reason for using one server rather than two servers to compare is to guarantee the same data source and same segment state after compaction. Test Sequence: 1. Go 1.20 Initial Run: Insert data, build index, load index, and search. 2. Go 1.20 Rebuild: Rebuild the index with the same dataset, load index, and search. 3. Go 1.21 Load: Upload to Go 1.21 within the server. Then load the index from the second run, and search. 4. Go 1.21 Rebuild: Rebuild the index with the same dataset, load index, and search. Search Metrics: | Metric | Go 1.20 | Go 1.20 Rebuild Index | Go 1.21 | Go 1.21 Rebuild Index | |----------------------------|------------------|-----------------|------------------|-----------------| | `search requests` | 10,942,683 | 16,131,726 | 16,200,887 | 16,331,052 | | `search fails` | 0 | 0 | 0 | 0 | | `search RT_avg` (ms) | 16.44 | 11.15 | 11.11 | 11.02 | | `search RT_min` (ms) | 1.30 | 1.28 | 1.31 | 1.26 | | `search RT_max` (ms) | 446.61 | 233.22 | 235.90 | 147.93 | | `search TP50` (ms) | 11.74 | 10.46 | 10.43 | 10.35 | | `search TP99` (ms) | 92.30 | 25.76 | 25.36 | 25.23 | | `search RPS` | 3,039 | 4,481 | 4,500 | 4,536 | ### Key Findings The benchmark tests reveal that the index build time with Go 1.20 at 340.39 ms and Go 1.21 at 337.60 ms demonstrated negligible performance variance in index construction. However, Go 1.21 offers slightly better performance in search operations compared to Go 1.20, with improvements in handling concurrent tasks and reducing response times. ## Search Benchmark Report By VectorDb Bench Follow [VectorDBBench](https://github.com/zilliztech/VectorDBBench?tab=readme-ov-file) to create a VectorDb Bench test for Go 1.20 and Go 1.21. We test the search performance with Go 1.20 and Go 1.21 (without PGO) on the Milvus Standalone system. The tests were conducted using the Cohere dataset with 1 million entries in a 768-dimensional space, utilizing the COSINE metric type. Search Metrics: Metric | Go 1.20 | Go 1.21 without PGO -- | -- | -- Load Duration (seconds) | 1195.95 | 976.37 Queries Per Second (QPS) | 841.62 | 875.89 99th Percentile Serial Latency (seconds) | 0.0047 | 0.0076 Recall | 0.9487 | 0.9489 ### Key Findings Go 1.21 indicates faster index loading times and larger search QPS handling. ## PGO Performance Test Milvus has already added [net/http/pprof](https://pkg.go.dev/net/http/pprof) in the metrics. So we can curl the CPU profile directly by running `curl -o default.pgo "http://${MILVUS_SERVER_IP}:${MILVUS_SERVER_PORT}/debug/pprof/profile?seconds=${TIME_SECOND}"` to collect the profile as the default.pgo during the first search. Then I build Milvus with PGO and use the same index to run the search again. The result is as below: Search Metrics | Metric | Go 1.21 Without PGO | Go 1.21 With PGO | Change (%) | |---------------------------------------------|------------------|-----------------|------------| | `search Requests` | 2,644,583 | 2,837,726 | +7.30% | | `search Fails` | 0 | 0 | N/A | | `search RT_avg` (ms) | 11.34 | 10.57 | -6.78% | | `search RT_min` (ms) | 1.39 | 1.32 | -5.18% | | `search RT_max` (ms) | 349.72 | 143.72 | -58.91% | | `search TP50` (ms) | 10.57 | 9.93 | -6.05% | | `search TP99` (ms) | 26.14 | 24.16 | -7.56% | | `search RPS` | 4,407 | 4,729 | +7.30% | ### Key Findings PGO led to a notable enhancement in search performance, particularly in reducing the maximum response time by 58% and increasing the search QPS by 7.3%. ### Further Analysis Generate a diff flame graphs between two CPU profiles by running `go tool pprof -http=:8000 -diff_base nopgo.pgo pgo.pgo -normalize` <img width="1894" alt="goprofiling" src="https://github.com/milvus-io/milvus/assets/167743503/ab9e91eb-95c7-4963-acd9-d1c3c73ee010"> Further insight of HnswIndexNode and Milvus Search Handler <img width="1906" alt="hnsw" src="https://github.com/milvus-io/milvus/assets/167743503/a04cf4a0-7c97-4451-b3cf-98afc20a0b05"> <img width="1873" alt="search_handler" src="https://github.com/milvus-io/milvus/assets/167743503/5f4d3982-18dd-4115-8e76-460f7f534c7f"> After applying PGO to the Milvus server, the CPU utilization of the faiss::fvec_L2 function has decreased. This optimization significantly enhances the performance of the [HnswIndexNode::Search::searchKnn](https://github.com/zilliztech/knowhere/blob/e0c9c41aa22d8f6e6761a0a54460e4573de15bfe/src/index/hnsw/hnsw.cc#L203) method, which is frequently invoked by Knowhere during high-concurrency searches. As the explanation from Go release notes, the function might be more aggressively inlined by Go compiler during the second build with the CPU profiling collected from the first run. As a result, the search handler efficiency within Milvus DataNode has improved, allowing the server to process a higher number of search queries per second (QPS). # Conclusion The combination of Go 1.21 and PGO has led to substantial enhancements in search performance for Milvus server, particularly in terms of search QPS and response times, making it more efficient for handling high-concurrency search operations. Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
2024-05-22 13:21:39 +08:00
GO111MODULE=on $(GO) build -pgo=$(PGO_PATH)/default.pgo -ldflags="-r $${RPATH} -X '$(OBJPREFIX).BuildTags=$(BUILD_TAGS)' -X '$(OBJPREFIX).BuildTime=$(BUILD_TIME)' -X '$(OBJPREFIX).GitCommit=$(GIT_COMMIT)' -X '$(OBJPREFIX).GoVersion=$(GO_VERSION)'" \
-tags dynamic -o $(INSTALL_PATH)/mmap-migration $(MMAP_MIGRATION_PATH)/main.go 1>/dev/null