const { Table, DateVector, FloatVector, predicate} = require("apache-arrow")
Function to build a table from the standard Pond TimeSeries JSON format:
const makeTable = (timeseries) => {
const { name, columns, points } = timeseries;
const length = points.length;
// Timestamp array
const times = new Array(length);
// Setup named channels of Float32Arrays
const channels = {};
columns.forEach(c => (channels[c] = new Float32Array(length)));
// Fill each channel
points.forEach((point, pointIndex) => {
const [timestamp, ...values] = point;
times[pointIndex] = timestamp;
values.forEach((value, valueIndex) => {
const channelName = columns[valueIndex];
channels[channelName][pointIndex] = value;
});
});
const fieldNames = ["time", ...Object.keys(channels)];
const dateVector = DateVector.from(times);
const valueVectors = Object.keys(channels).map(c =>
FloatVector.from(channels[c])
);
const table = Table.new([dateVector, ...valueVectors], fieldNames);
return table;
}
Here's some JSON, let's try it:
const data = {
name: "weather",
columns: ["temperature", "pressure"],
points: [
[1594491206349, 92, 29.1],
[1594491356349, 95, 28.8],
[1594491456349, 91, 28.3],
[1594491556349, 88, 27.2]
]
};
const table = makeTable(data);
Print out what's in the table, at least I think toArray() should give me a list of Rows and then each of those has a toJSON() function on it, or you can use row.get("temperature") etc.
table.toArray().map(row => row.toJSON())
Ok, the big test, make a filter for pressures less than 28.5, of which there should be 2:
filtered = table.filter(predicate.col("pressure").lt(28.5))
Get the count of the filtered table:
filtered.count()
Looks good! But then when I iterate over the filtered table I get all rows:
filtered.toArray().map(row => row.toJSON())
That doesn't seem right. Scanning does work however:
filteredResult = [];
filtered.scan((idx) => {
const row = filtered.get(idx).toJSON();
filteredResult.push(row)
});
filteredResult;
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