BigQuery schema for benchmark-tools dashboard.

PiperOrigin-RevId: 303805784

1 files changed, 121 insertions, 0 deletions

diff --git a/tools/bigquery/bigquery.go b/tools/bigquery/bigquery.go
new file mode 100644
index 000000000..56f0dc5c9
--- /dev/null
+++ b/tools/bigquery/bigquery.go
@@ -0,0 +1,121 @@
+// Copyright 2020 The gVisor Authors.
+//
+// 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.
+
+// Package bigquery defines a BigQuery schema for benchmarks.
+//
+// This package contains a schema for BigQuery and methods for publishing
+// benchmark data into tables.
+package bigquery
+
+import (
+	"context"
+	"fmt"
+	"strings"
+	"time"
+
+	bq "cloud.google.com/go/bigquery"
+)
+
+// Benchmark is the top level structure of recorded benchmark data. BigQuery
+// will infer the schema from this.
+type Benchmark struct {
+	Name      string    `bq:"name"`
+	Timestamp time.Time `bq:"timestamp"`
+	Official  bool      `bq:"official"`
+	Metric    []*Metric `bq:"metric"`
+	Metadata  *Metadata `bq:"metadata"`
+}
+
+// Metric holds the actual metric data and unit information for this benchmark.
+type Metric struct {
+	Name   string  `bq:"name"`
+	Unit   string  `bq:"unit"`
+	Sample float64 `bq:"sample"`
+}
+
+// Metadata about this benchmark.
+type Metadata struct {
+	CL          string `bq:"changelist"`
+	IterationID string `bq:"iteration_id"`
+	PendingCL   string `bq:"pending_cl"`
+	Workflow    string `bq:"workflow"`
+	Platform    string `bq:"platform"`
+	Gofer       string `bq:"gofer"`
+}
+
+// InitBigQuery initializes a BigQuery dataset/table in the project. If the dataset/table already exists, it is not duplicated.
+func InitBigQuery(ctx context.Context, projectID, datasetID, tableID string) error {
+	client, err := bq.NewClient(ctx, projectID)
+	if err != nil {
+		return fmt.Errorf("failed to initialize client on project %s: %v", projectID, err)
+	}
+	defer client.Close()
+
+	dataset := client.Dataset(datasetID)
+	if err := dataset.Create(ctx, nil); err != nil && !checkDuplicateError(err) {
+		return fmt.Errorf("failed to create dataset: %s: %v", datasetID, err)
+	}
+
+	table := dataset.Table(tableID)
+	schema, err := bq.InferSchema(Benchmark{})
+	if err != nil {
+		return fmt.Errorf("failed to infer schema: %v", err)
+	}
+
+	if err := table.Create(ctx, &bq.TableMetadata{Schema: schema}); err != nil && !checkDuplicateError(err) {
+		return fmt.Errorf("failed to create table: %s: %v", tableID, err)
+	}
+	return nil
+}
+
+// AddMetric adds a metric to an existing Benchmark.
+func (bm *Benchmark) AddMetric(metricName, unit string, sample float64) {
+	m := &Metric{
+		Name:   metricName,
+		Unit:   unit,
+		Sample: sample,
+	}
+	bm.Metric = append(bm.Metric, m)
+}
+
+// NewBenchmark initializes a new benchmark.
+func NewBenchmark(name string, official bool) *Benchmark {
+	return &Benchmark{
+		Name:      name,
+		Timestamp: time.Now().UTC(),
+		Official:  official,
+		Metric:    make([]*Metric, 0),
+	}
+}
+
+// SendBenchmarks sends the slice of benchmarks to the BigQuery dataset/table.
+func SendBenchmarks(ctx context.Context, benchmarks []*Benchmark, projectID, datasetID, tableID string) error {
+	client, err := bq.NewClient(ctx, projectID)
+	if err != nil {
+		return fmt.Errorf("Failed to initialize client on project: %s: %v", projectID, err)
+	}
+	defer client.Close()
+
+	uploader := client.Dataset(datasetID).Table(tableID).Uploader()
+	if err = uploader.Put(ctx, benchmarks); err != nil {
+		return fmt.Errorf("failed to upload benchmarks to proejct %s, table %s.%s: %v", projectID, datasetID, tableID, err)
+	}
+
+	return nil
+}
+
+// BigQuery will error "409" for duplicate tables and datasets.
+func checkDuplicateError(err error) bool {
+	return strings.Contains(err.Error(), "googleapi: Error 409: Already Exists")
+}