3. Define the aggregator and tally functions¶
This article is part of the beginner tutorial on creating a totally decentralized Bitcoin price feed on Ethereum with Solidity and Witnet.
What is an aggregator?¶
Aggregators define how to reduce or merge the result of multiple sources
into a single data point. They are similar to JavaScript's .reduce()
method or the fold higher-order function from many programming
languages.
In addition, aggregation functions give the chance to filter out any outliers by using one or more statistical primitives.
- Every Witnet request needs to have exactly one aggregator function.
- Aggregators contain zero, one or more filters.
- Aggregators contain exactly one reducer.
- When a Witnet node gets a request assigned for resolution, it
retrieves every source, applies the source companion scripts on the
retrieved data, collects the results into an
Array, and then apply the aggregator on it, first running the filters and later the reducer.
What is a tally function?¶
Tallies are really similar to aggregators, but instead of merging multiple sources, they merge the results reported by multiple Witnet nodes.
Let's average multiple sources¶
In this case, you will be using an aggregator that filters out any
outliers coming from the two sources that you defined before, and
returns the average mean of the Float values that pass the filter:
// Filters out any value that is more than 1.5 times the standard
// deviation away from the average, then computes the average mean of the
// values that pass the filter.
const aggregator = new Witnet.Aggregator({
filters: [
[Witnet.Types.FILTERS.deviationStandard, 1.5]
],
reducer: Witnet.Types.REDUCERS.averageMean
})
That will be enough to reduce the Array containing the Float
responses of the two sources into a single Float that represents the
average mean of non-outliers values. You can now continue with the tally
function.
Tally by average¶
For this tutorial, we will be using a tally function that is quite similar to the aggregation function:
// Filters out any value that is more than 1.5 times the standard
// deviation away from the average, then computes the average mean of the
// values that pass the filter.
const tally = new Witnet.Tally({
filters: [
[Witnet.Types.FILTERS.deviationStandard, 1.5]
],
reducer: Witnet.Types.REDUCERS.averageMean
})
Quick recap¶
At this point, requests/BitcoinPrice.js should look like this:
import * as Witnet from "witnet-requests"
// Retrieves USD price of a bitcoin from the BitStamp API
const bitstamp = new Witnet.Source("https://www.bitstamp.net/api/ticker/")
.parseJSONMap() // Parse a `Map` from the retrieved `String`
.getFloat("last") // Get the `Float` value associated to the `last` key
// Retrieves USD price of a bitcoin from CoinDesk's "bitcoin price index" API
// The JSON here is a bit more complex, thus more operators are needed
const coindesk = new Witnet.Source("https://api.coindesk.com/v1/bpi/currentprice.json")
.parseJSONMap() // Parse a `Map` from the retrieved `String`
.getMap("bpi") // Get the `Map` value associated to the `bpi` key
.getMap("USD") // Get the `Map` value associated to the `USD` key
.getFloat("rate_float") // Get the `Float` value associated to the `rate_float` key
// Filters out any value that is more than 1.5 times the standard
// deviation away from the average, then computes the average mean of the
// values that pass the filter.
const aggregator = new Witnet.Aggregator({
filters: [
[Witnet.Types.FILTERS.deviationStandard, 1.5]
],
reducer: Witnet.Types.REDUCERS.averageMean
})
// Filters out any value that is more than 1.5 times the standard
// deviation away from the average, then computes the average mean of the
// values that pass the filter.
const tally = new Witnet.Tally({
filters: [
[Witnet.Types.FILTERS.deviationStandard, 1.5]
],
reducer: Witnet.Types.REDUCERS.averageMean
})
Now it is time to put everything together and fine-tune the request.