@netdata/charts
Version:
Netdata frontend SDK and chart utilities
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JavaScript
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function _nonIterableSpread() { throw new TypeError("Invalid attempt to spread non-iterable instance.\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method."); }
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import makeDefaultSDK from "../../../makeDefaultSDK";
import { getSparklineBatchAttributes, getSparklineBatchDimensions, getSparklineDataFetcher, normalizeSparklinePayload, sparklineRequestLimits } from "./sparklineData";
var makePayload = function makePayload(dimensions) {
var _ref = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {},
units = _ref.units;
return {
view: {
units: "requests/s",
dimensions: {
units: units || dimensions.map(function () {
return "requests/s";
})
}
},
result: {
labels: ["time"].concat(_toConsumableArray(dimensions)),
point: {
value: 0,
anomalyRate: 1
},
data: [[1000].concat(_toConsumableArray(dimensions.map(function (dimension, index) {
return [index + 1, 0];
}))), [1005].concat(_toConsumableArray(dimensions.map(function (dimension, index) {
return [index + 2, 0];
})))]
}
};
};
var makeOwner = function makeOwner(getChart) {
var sdk = makeDefaultSDK();
var owner = sdk.makeChart({
getChart: getChart,
attributes: {
after: 100,
agent: "agent",
before: 200,
context: "main-context",
contextScope: ["main-context"],
groupingMethod: "average",
groupingTime: 5,
host: "host",
points: 300,
selectedNodes: ["selected-node"]
}
});
sdk.appendChild(owner);
return {
sdk: sdk,
owner: owner
};
};
var makeDimension = function makeDimension(index) {
var overrides = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {};
return _objectSpread({
rowId: JSON.stringify(["dimension", index]),
context: "context",
dimension: "dimension-".concat(String(index).padStart(3, "0")),
nodeId: "node"
}, overrides);
};
var makeAttrs = function makeAttrs(owner, index) {
return getSparklineBatchAttributes(owner, [makeDimension(index)]);
};
describe("sparkline batch requests", function () {
it("builds deterministic bounded batches for one context and node", function () {
var dimensions = Array.from({
length: 120
}, function (_, index) {
return makeDimension(index);
}).reverse();
dimensions.push(makeDimension(200, {
context: "other-context"
}));
dimensions.push(makeDimension(201, {
nodeId: "other-node"
}));
var batch = getSparklineBatchDimensions(dimensions[44], dimensions);
expect(batch).toHaveLength(sparklineRequestLimits.batchDimensions);
expect(batch[0].dimension).toBe("dimension-119");
expect(batch.at(-1).dimension).toBe("dimension-070");
expect(batch.every(function (item) {
return item.context === "context" && item.nodeId === "node";
})).toBe(true);
expect(getSparklineBatchDimensions(dimensions[43], dimensions)).toBe(batch);
});
it("scopes one request to the batch dimensions and caps its points", function () {
var _makeOwner = makeOwner(/*#__PURE__*/_asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee() {
return _regenerator().w(function (_context) {
while (1) switch (_context.n) {
case 0:
return _context.a(2, makePayload([]));
}
}, _callee);
}))),
owner = _makeOwner.owner;
var dimensions = [makeDimension(2), makeDimension(1), makeDimension(1)];
expect(getSparklineBatchAttributes(owner, dimensions)).toMatchObject({
after: 100,
before: 200,
context: null,
contextScope: ["context"],
eliminateZeroDimensions: false,
groupBy: ["dimension"],
nodesScope: ["node"],
points: sparklineRequestLimits.points,
postGroupBy: [],
postGroupByLabel: [],
selectedContexts: [],
selectedDimensions: ["dimension-001", "dimension-002"],
selectedInstances: [],
selectedLabels: [],
selectedNodes: [],
showPostAggregations: false
});
});
});
describe("normalizeSparklinePayload", function () {
it("extracts compact series directly from JSON2 cells", function () {
var payload = {
view: {
dimensions: {
units: ["microseconds", "bytes"]
}
},
result: {
labels: ["time", "latency", "traffic"],
point: {
value: 0,
anomalyRate: 1
},
data: [[1000, [1, 0], [null, 0]], [1005, [3, 0], [8, 0]]]
}
};
var result = normalizeSparklinePayload(payload);
expect(result.get("latency")).toEqual({
values: [1, 3],
min: 1,
max: 3,
latest: 3,
unit: "us"
});
expect(result.get("traffic")).toEqual({
values: [null, 8],
min: 8,
max: 8,
latest: 8,
unit: "By"
});
});
it("rejects responses without chart labels and data", function () {
expect(function () {
return normalizeSparklinePayload({});
}).toThrow("Invalid sparkline response");
});
});
describe("getSparklineDataFetcher", function () {
it("deduplicates in-flight requests and reuses normalized cached responses", /*#__PURE__*/_asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee3() {
var calls, _makeOwner2, owner, getData, attrs, _yield$Promise$all, _yield$Promise$all2, first, second, cached;
return _regenerator().w(function (_context3) {
while (1) switch (_context3.n) {
case 0:
calls = 0;
_makeOwner2 = makeOwner(/*#__PURE__*/function () {
var _ref4 = _asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee2(requestChart) {
return _regenerator().w(function (_context2) {
while (1) switch (_context2.n) {
case 0:
calls++;
return _context2.a(2, makePayload(requestChart.getAttribute("selectedDimensions")));
}
}, _callee2);
}));
return function (_x) {
return _ref4.apply(this, arguments);
};
}()), owner = _makeOwner2.owner;
getData = getSparklineDataFetcher(owner);
attrs = makeAttrs(owner, 1);
_context3.n = 1;
return Promise.all([getData(attrs), getData(attrs)]);
case 1:
_yield$Promise$all = _context3.v;
_yield$Promise$all2 = _slicedToArray(_yield$Promise$all, 2);
first = _yield$Promise$all2[0];
second = _yield$Promise$all2[1];
_context3.n = 2;
return getData(attrs);
case 2:
cached = _context3.v;
expect(first).toBe(second);
expect(cached).toBe(first);
expect(cached.get("dimension-001").latest).toBe(2);
expect(calls).toBe(1);
case 3:
return _context3.a(2);
}
}, _callee3);
})));
it("uses a lightweight request facade without adding SDK child charts", /*#__PURE__*/_asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee5() {
var received, _makeOwner3, sdk, owner, getData, attrs;
return _regenerator().w(function (_context5) {
while (1) switch (_context5.n) {
case 0:
_makeOwner3 = makeOwner(/*#__PURE__*/function () {
var _ref6 = _asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee4(requestChart, options) {
return _regenerator().w(function (_context4) {
while (1) switch (_context4.n) {
case 0:
received = {
attrs: options.attrs,
filteredNodes: requestChart.getFilteredNodeIds(),
selectedNodes: requestChart.getAttribute("selectedNodes")
};
return _context4.a(2, makePayload(requestChart.getAttribute("selectedDimensions")));
}
}, _callee4);
}));
return function (_x2, _x3) {
return _ref6.apply(this, arguments);
};
}()), sdk = _makeOwner3.sdk, owner = _makeOwner3.owner;
getData = getSparklineDataFetcher(owner);
attrs = makeAttrs(owner, 1);
_context5.n = 1;
return getData(attrs);
case 1:
expect(received).toMatchObject({
attrs: attrs,
filteredNodes: [],
selectedNodes: []
});
expect(sdk.getRoot().getChildren()).toEqual([owner]);
expect(owner.getAttribute("selectedNodes")).toEqual(["selected-node"]);
expect(owner.getAttribute("context")).toBe("main-context");
case 2:
return _context5.a(2);
}
}, _callee5);
})));
it("limits concurrent transport requests", /*#__PURE__*/_asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee7() {
var active, maxActive, _makeOwner4, owner, getData, requests;
return _regenerator().w(function (_context7) {
while (1) switch (_context7.n) {
case 0:
active = 0;
maxActive = 0;
_makeOwner4 = makeOwner(/*#__PURE__*/function () {
var _ref8 = _asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee6(requestChart) {
return _regenerator().w(function (_context6) {
while (1) switch (_context6.n) {
case 0:
active++;
maxActive = Math.max(maxActive, active);
_context6.n = 1;
return new Promise(function (resolve) {
return setTimeout(resolve, 5);
});
case 1:
active--;
return _context6.a(2, makePayload(requestChart.getAttribute("selectedDimensions")));
}
}, _callee6);
}));
return function (_x4) {
return _ref8.apply(this, arguments);
};
}()), owner = _makeOwner4.owner;
getData = getSparklineDataFetcher(owner);
requests = Array.from({
length: 20
}, function (_, index) {
return getData(makeAttrs(owner, index));
});
_context7.n = 1;
return Promise.all(requests);
case 1:
expect(maxActive).toBe(sparklineRequestLimits.concurrency);
case 2:
return _context7.a(2);
}
}, _callee7);
})));
it("drops queued requests when their consumer aborts", /*#__PURE__*/_asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee8() {
var calls, resolvers, _makeOwner5, owner, getData, activeRequests, controller, queuedRequest;
return _regenerator().w(function (_context8) {
while (1) switch (_context8.n) {
case 0:
calls = 0;
resolvers = [];
_makeOwner5 = makeOwner(function (requestChart) {
return new Promise(function (resolve) {
calls++;
resolvers.push(function () {
return resolve(makePayload(requestChart.getAttribute("selectedDimensions")));
});
});
}), owner = _makeOwner5.owner;
getData = getSparklineDataFetcher(owner);
activeRequests = Array.from({
length: sparklineRequestLimits.concurrency
}, function (_, index) {
return getData(makeAttrs(owner, index));
});
controller = new AbortController();
queuedRequest = getData(makeAttrs(owner, 99), {
signal: controller.signal
});
controller.abort();
_context8.n = 1;
return expect(queuedRequest).rejects.toMatchObject({
name: "AbortError"
});
case 1:
resolvers.forEach(function (resolve) {
return resolve();
});
_context8.n = 2;
return Promise.all(activeRequests);
case 2:
expect(calls).toBe(sparklineRequestLimits.concurrency);
case 3:
return _context8.a(2);
}
}, _callee8);
})));
it("evicts the least recently used completed responses", /*#__PURE__*/_asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee0() {
var calls, _makeOwner6, owner, getData, first, index;
return _regenerator().w(function (_context0) {
while (1) switch (_context0.n) {
case 0:
calls = 0;
_makeOwner6 = makeOwner(/*#__PURE__*/function () {
var _ref1 = _asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee9(requestChart) {
return _regenerator().w(function (_context9) {
while (1) switch (_context9.n) {
case 0:
calls++;
return _context9.a(2, makePayload(requestChart.getAttribute("selectedDimensions")));
}
}, _callee9);
}));
return function (_x5) {
return _ref1.apply(this, arguments);
};
}()), owner = _makeOwner6.owner;
getData = getSparklineDataFetcher(owner);
first = makeAttrs(owner, 0);
_context0.n = 1;
return getData(first);
case 1:
index = 1;
case 2:
if (!(index <= sparklineRequestLimits.cache)) {
_context0.n = 4;
break;
}
_context0.n = 3;
return getData(makeAttrs(owner, index));
case 3:
index++;
_context0.n = 2;
break;
case 4:
_context0.n = 5;
return getData(first);
case 5:
expect(calls).toBe(sparklineRequestLimits.cache + 2);
case 6:
return _context0.a(2);
}
}, _callee0);
})));
});