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client.go
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// Copyright Splunk, Inc.
// Copyright The OpenTelemetry 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 httpsinkexporter
import (
"context"
"fmt"
"strings"
"time"
"github.com/jaegertracing/jaeger/model"
"go.opentelemetry.io/collector/pdata/pmetric"
)
type client struct {
spans chan *model.Batch
metrics chan pmetric.Metrics
opts options
stopped bool
}
func newClient(opts options) *client {
return &client{
spans: make(chan *model.Batch),
metrics: make(chan pmetric.Metrics),
opts: opts,
}
}
func (c *client) response(ctx context.Context) ([]byte, error) {
// TODO: add support to filter spans by attributes
defer func() {
c.stopped = true
}()
results := []string{}
received := 0
done := make(chan struct{})
for {
select {
case batch := <-c.spans:
batch = c.filterSpans(batch)
for _, span := range batch.Spans {
json, err := spanMarshaler.MarshalToString(span)
if err != nil {
return nil, err
}
results = append(results, json)
received++
if received == c.opts.count {
close(done)
}
}
case md := <-c.metrics:
md = c.filterMetrics(md)
count := md.MetricCount()
if count > 0 {
json, err := metricMarshaler.MarshalMetrics(md)
if err != nil {
return nil, err
}
results = append(results, string(json))
received += count
}
if received >= c.opts.count {
close(done)
}
case <-time.After(c.opts.timeout):
return nil, fmt.Errorf("timed out while waiting for results")
case <-ctx.Done():
return nil, fmt.Errorf("context deadline exceeded")
case <-done:
result := "[" + strings.Join(results, ",") + "]"
return []byte(result), nil
}
}
}
func (c *client) filterSpans(b *model.Batch) *model.Batch {
spans := []*model.Span{}
for _, span := range b.Spans {
match := c.filterByName(span.OperationName)
if match {
spans = append(spans, span)
}
}
return &model.Batch{
Process: b.Process,
Spans: spans,
}
}
func (c *client) filterMetrics(md pmetric.Metrics) pmetric.Metrics {
m := pmetric.NewMetrics()
md.CopyTo(m)
for i := 0; i < m.ResourceMetrics().Len(); i++ {
rm := m.ResourceMetrics().At(i)
for j := 0; j < rm.ScopeMetrics().Len(); j++ {
sm := rm.ScopeMetrics().At(j)
sm.Metrics().RemoveIf(func(metric pmetric.Metric) bool {
matched := c.filterByName(metric.Name()) || c.filterMetricByAttrs(metric)
return !matched
})
}
}
return m
}
func (c *client) filterByName(name string) bool {
if len(c.opts.names) == 0 {
return true
}
for _, n := range c.opts.names {
if name == n {
return true
}
}
return false
}
func (c *client) filterMetricByAttrs(metric pmetric.Metric) bool {
if len(c.opts.attrs) == 0 {
return true
}
switch metric.Type() {
case pmetric.MetricTypeGauge:
return filterMetricByAttr[pmetric.NumberDataPoint, pmetric.NumberDataPointSlice](metric.Gauge(), c.opts.attrs)
case pmetric.MetricTypeSum:
return filterMetricByAttr[pmetric.NumberDataPoint, pmetric.NumberDataPointSlice](metric.Sum(), c.opts.attrs)
case pmetric.MetricTypeHistogram:
return filterMetricByAttr[pmetric.HistogramDataPoint, pmetric.HistogramDataPointSlice](metric.Histogram(), c.opts.attrs)
case pmetric.MetricTypeExponentialHistogram:
return filterMetricByAttr[pmetric.ExponentialHistogramDataPoint, pmetric.ExponentialHistogramDataPointSlice](metric.ExponentialHistogram(), c.opts.attrs)
case pmetric.MetricTypeSummary:
return filterMetricByAttr[pmetric.SummaryDataPoint, pmetric.SummaryDataPointSlice](metric.Summary(), c.opts.attrs)
}
return false
}