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@netdata/charts

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Netdata frontend SDK and chart utilities

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"use strict"; var _react = _interopRequireDefault(require("react")); var _react2 = require("@testing-library/react"); require("@testing-library/jest-dom"); var _netdataUi = require("@netdata/netdata-ui"); var _testUtilities = require("@jest/testUtilities"); var _table = _interopRequireDefault(require("./table")); var _jsxRuntime = require("react/jsx-runtime"); function _interopRequireDefault(e) { return e && e.__esModule ? e : { "default": e }; } function _typeof(o) { "@babel/helpers - typeof"; return _typeof = "function" == typeof Symbol && "symbol" == typeof Symbol.iterator ? function (o) { return typeof o; } : function (o) { return o && "function" == typeof Symbol && o.constructor === Symbol && o !== Symbol.prototype ? "symbol" : typeof o; }, _typeof(o); } function _toConsumableArray(r) { return _arrayWithoutHoles(r) || _iterableToArray(r) || _unsupportedIterableToArray(r) || _nonIterableSpread(); } 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."); } function _unsupportedIterableToArray(r, a) { if (r) { if ("string" == typeof r) return _arrayLikeToArray(r, a); var t = {}.toString.call(r).slice(8, -1); return "Object" === t && r.constructor && (t = r.constructor.name), "Map" === t || "Set" === t ? Array.from(r) : "Arguments" === t || /^(?:Ui|I)nt(?:8|16|32)(?:Clamped)?Array$/.test(t) ? _arrayLikeToArray(r, a) : void 0; } } function _iterableToArray(r) { if ("undefined" != typeof Symbol && null != r[Symbol.iterator] || null != r["@@iterator"]) return Array.from(r); } function _arrayWithoutHoles(r) { if (Array.isArray(r)) return _arrayLikeToArray(r); } function _arrayLikeToArray(r, a) { (null == a || a > r.length) && (a = r.length); for (var e = 0, n = Array(a); e < a; e++) n[e] = r[e]; return n; } function _regenerator() { /*! regenerator-runtime -- Copyright (c) 2014-present, Facebook, Inc. -- license (MIT): https://github.com/babel/babel/blob/main/packages/babel-helpers/LICENSE */ var e, t, r = "function" == typeof Symbol ? 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String : Number)(t); } var makeDimension = function makeDimension(contextIndex, dimensionIndex) { var overrides = arguments.length > 2 && arguments[2] !== undefined ? arguments[2] : {}; return _objectSpread({ rowId: JSON.stringify(["dimension", contextIndex, dimensionIndex]), kind: "dimension", dimension: "dimension-".concat(contextIndex, "-").concat(String(dimensionIndex).padStart(5, "0")), dimensionName: "Dimension ".concat(contextIndex, "-").concat(dimensionIndex), context: "context-".concat(contextIndex), contextName: "Context ".concat(contextIndex), nodeId: "node-".concat(dimensionIndex), nodeName: "Node ".concat(dimensionIndex), correlationWeight: 0.005, correlationStrength: "Strong", percentChange: 5 }, overrides); }; var makeData = function makeData(contextCount) { return Array.from({ length: contextCount }, function (_, contextIndex) { return { rowId: JSON.stringify(["context", contextIndex]), kind: "context", context: "context-".concat(contextIndex), contextName: "Context ".concat(contextIndex), minWeight: 0.005, count: 2, children: [makeDimension(contextIndex, 0), makeDimension(contextIndex, 1)] }; }); }; describe("CorrelationTable", function () { it("virtualizes high-cardinality rows and persists expansion in chart attributes", /*#__PURE__*/_asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee() { var data, _renderWithChart, chart, user; return _regenerator().w(function (_context) { while (1) switch (_context.n) { case 0: data = makeData(1000); _renderWithChart = (0, _testUtilities.renderWithChart)(/*#__PURE__*/(0, _jsxRuntime.jsx)(_netdataUi.Box, { height: "400px", children: /*#__PURE__*/(0, _jsxRuntime.jsx)(_table["default"], { data: data }) }), { attributes: { correlate: { expanded: {} } } }), chart = _renderWithChart.chart, user = _renderWithChart.user; expect(_react2.screen.getByText("Found 2000 correlated dimensions across 1000 contexts")).toBeInTheDocument(); _context.n = 1; return (0, _react2.waitFor)(function () { var renderedRows = _react2.screen.queryAllByTestId("netdata-table-row"); expect(renderedRows.length).toBeGreaterThan(0); expect(renderedRows.length).toBeLessThan(data.length); }); case 1: _context.n = 2; return user.click(_react2.screen.getByRole("button", { name: "Expand all" })); case 2: expect(chart.getAttribute("correlate.expanded")).toBe(true); expect(_react2.screen.queryAllByTestId("netdata-table-row").length).toBeLessThan(3000); case 3: return _context.a(2); } }, _callee); }))); it("fetches and renders trends only for the visible batch", /*#__PURE__*/_asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee3() { var children, data, requests, _makeTestChart, sdk, chart, _renderWithChart2, user, table; return _regenerator().w(function (_context3) { while (1) switch (_context3.n) { case 0: children = Array.from({ length: 5000 }, function (_, index) { return makeDimension(0, index, { nodeId: "shared-node" }); }); data = [{ rowId: JSON.stringify(["context", 0]), kind: "context", context: "context-0", contextName: "Context 0", minWeight: 0.005, count: children.length, children: children }]; requests = []; _makeTestChart = (0, _testUtilities.makeTestChart)({ attributes: { after: 100, before: 200, correlate: { expanded: {} }, points: 300 } }), sdk = _makeTestChart.sdk, chart = _makeTestChart.chart; chart.getChart = /*#__PURE__*/function () { var _ref3 = _asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee2(requestChart) { var dimensions; return _regenerator().w(function (_context2) { while (1) switch (_context2.n) { case 0: dimensions = requestChart.getAttribute("selectedDimensions"); requests.push(dimensions); return _context2.a(2, { view: { dimensions: { units: dimensions.map(function () { return "requests/s"; }) } }, result: { labels: ["time"].concat(_toConsumableArray(dimensions)), point: { value: 0 }, data: [[1000].concat(_toConsumableArray(dimensions.map(function (dimension, index) { return [index + 1]; }))), [1005].concat(_toConsumableArray(dimensions.map(function (dimension, index) { return [index + 2]; })))] } }); } }, _callee2); })); return function (_x) { return _ref3.apply(this, arguments); }; }(); _renderWithChart2 = (0, _testUtilities.renderWithChart)(/*#__PURE__*/(0, _jsxRuntime.jsx)(_netdataUi.Box, { height: "400px", children: /*#__PURE__*/(0, _jsxRuntime.jsx)(_table["default"], { data: data }) }), { chart: chart }), user = _renderWithChart2.user; _context3.n = 1; return user.click(_react2.screen.getByRole("button", { name: "Expand all" })); case 1: table = _react2.screen.getByTestId("netdata-table"); table.scrollTop = 35; _react2.fireEvent.scroll(table); _context3.n = 2; return (0, _react2.waitFor)(function () { return expect(_react2.screen.getAllByRole("img", { name: "Metric trend" })).not.toHaveLength(0); }); case 2: _context3.n = 3; return (0, _react2.waitFor)(function () { return expect(requests).toHaveLength(1); }); case 3: expect(requests[0]).toHaveLength(50); expect(_react2.screen.getAllByRole("img", { name: "Metric trend" }).length).toBeLessThan(children.length); expect(sdk.getRoot().getChildren()).toEqual([chart]); case 4: return _context3.a(2); } }, _callee3); }))); it("searches visible metric identity text and ignores raw measurements", /*#__PURE__*/_asyncToGenerator(/*#__PURE__*/_regenerator().m(function _callee4() { var originalExpanded, data, _renderWithChart3, chart, user, search, filteredSearch; return _regenerator().w(function (_context4) { while (1) switch (_context4.n) { case 0: originalExpanded = { preserved: true }; data = [{ rowId: JSON.stringify(["context", "shared"]), kind: "context", context: "shared.context", contextName: "Shared context", minWeight: 0.005, count: 2, children: [makeDimension(0, 0, { dimension: "target-dimension", dimensionName: "Target metric", context: "target.context", contextName: "Shared context", nodeId: "target-node-id", nodeName: "Target node", correlationWeight: 0.005 }), makeDimension(0, 1, { dimension: "other-dimension", dimensionName: "Other metric", context: "other.context", contextName: "Shared context", nodeId: "other-node-id", nodeName: "Other node", correlationWeight: 0.007 })] }]; _renderWithChart3 = (0, _testUtilities.renderWithChart)(/*#__PURE__*/(0, _jsxRuntime.jsx)(_netdataUi.Box, { height: "400px", children: /*#__PURE__*/(0, _jsxRuntime.jsx)(_table["default"], { data: data }) }), { attributes: { correlate: { expanded: originalExpanded, search: "" } } }), chart = _renderWithChart3.chart, user = _renderWithChart3.user; search = _react2.screen.getByPlaceholderText("Search"); _context4.n = 1; return user.type(search, "Target node"); case 1: _context4.n = 2; return (0, _react2.waitFor)(function () { return expect(_react2.screen.getByText("Target metric")).toBeInTheDocument(); }); case 2: expect(_react2.screen.getByTestId("drawer-value-unit-detail")).toHaveTextContent("Strong"); expect(_react2.screen.queryByText("Other metric")).not.toBeInTheDocument(); expect(chart.getAttribute("correlate.expanded")).toEqual(originalExpanded); filteredSearch = _react2.screen.getByPlaceholderText("Search"); expect(filteredSearch).toHaveFocus(); _context4.n = 3; return user.clear(filteredSearch); case 3: _context4.n = 4; return user.type(filteredSearch, "0.005"); case 4: _context4.n = 5; return (0, _react2.waitFor)(function () { return expect(_react2.screen.queryByText("Shared context")).not.toBeInTheDocument(); }); case 5: return _context4.a(2); } }, _callee4); }))); });