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+# Batcher API Guide
+
+The batcher has two responsabilities: choosing which aggregator to choose for a metric instrument and store the last record for each metric ready to be exported.
+
+## Selecting a specific aggregator for metrics
+
+Sometimes you may want to use a specific aggregator for one of your metric, export a average of the last X values instead of just the last one.
+
+Here is what a aggregator that does that would looks like:
+```ts
+import { Aggregator } from '@opentelemetry/metrics';
+import { hrTime } from '@opentelemetry/core';
+
+export class AverageAggregator implements Aggregator {
+
+  private _values: number[] = [];
+  private _limit: number;
+
+  constructor (limit?: number) {
+    this._limit = limit ?? 10;
+  }
+
+  update (value: number) {
+    this._values.push(value);
+    if (this._values.length >= this._limit) {
+      this._values = this._values.slice(0, 10);
+    }
+  }
+
+  toPoint() {
+    const sum =this._values.reduce((agg, value) => {
+      agg += value;
+      return agg;
+    }, 0);
+    return {
+      value: this._values.length > 0 ? sum / this._values.length : 0,
+      timestamp: hrTime(),
+    }
+  }
+}
+```
+
+Now we will need to implement our own batcher to configure the sdk to use our new aggregator. To simplify even more, we will just extend the `UngroupedBatcher` (which is the default) to avoid re-implementing the whole `Aggregator` interface.
+
+Here the result:
+```ts
+import {
+  UngroupedBatcher,
+  MetricDescriptor,
+  CounterSumAggregator,
+  ObserverAggregator,
+  MeasureExactAggregator,
+} from '@opentelemetry/metrics';
+
+export class CustomBatcher extends UngroupedBatcher {
+  aggregatorFor (metricDescriptor: MetricDescriptor) {
+    if (metricDescriptor.labels === 'metricToBeAveraged') {
+      return new AverageAggregator(10);
+    }
+    // this is exactly what the "UngroupedBatcher" does, we will re-use it
+    // to fallback on the default behavior
+    switch (metricDescriptor.metricKind) {
+      case MetricKind.COUNTER:
+        return new CounterSumAggregator();
+      case MetricKind.OBSERVER:
+        return new ObserverAggregator();
+      default:
+        return new MeasureExactAggregator();
+    }
+  }
+}
+```
+
+Finally, we need to specify to the `MeterProvider` to use our `CustomBatcher` when creating new meter:
+
+```ts
+import {
+  UngroupedBatcher,
+  MetricDescriptor,
+  CounterSumAggregator,
+  ObserverAggregator,
+  MeasureExactAggregator,
+  MeterProvider,
+  Aggregator,
+} from '@opentelemetry/metrics';
+import { hrTime } from '@opentelemetry/core';
+
+export class AverageAggregator implements Aggregator {
+
+  private _values: number[] = [];
+  private _limit: number;
+
+  constructor (limit?: number) {
+    this._limit = limit ?? 10;
+  }
+
+  update (value: number) {
+    this._values.push(value);
+    if (this._values.length >= this._limit) {
+      this._values = this._values.slice(0, 10);
+    }
+  }
+
+  toPoint() {
+    const sum =this._values.reduce((agg, value) => {
+      agg += value;
+      return agg;
+    }, 0);
+    return {
+      value: this._values.length > 0 ? sum / this._values.length : 0,
+      timestamp: hrTime(),
+    }
+  }
+}
+
+export class CustomBatcher extends UngroupedBatcher {
+  aggregatorFor (metricDescriptor: MetricDescriptor) {
+    if (metricDescriptor.name === 'requests') {
+      return new AverageAggregator(10);
+    }
+    // this is exactly what the "UngroupedBatcher" does, we will re-use it
+    // to fallback on the default behavior
+    switch (metricDescriptor.metricKind) {
+      case MetricKind.COUNTER:
+        return new CounterSumAggregator();
+      case MetricKind.OBSERVER:
+        return new ObserverAggregator();
+      default:
+        return new MeasureExactAggregator();
+    }
+  }
+}
+
+const meter = new MeterProvider({
+  batcher: new CustomBatcher(),
+  interval: 1000,
+}).getMeter('example-custom-batcher');
+
+const requestsLatency = meter.createMeasure('requests', {
+  monotonic: true,
+  description: 'Average latency'
+});
+```
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