373 lines
13 KiB
JavaScript
373 lines
13 KiB
JavaScript
const DEFAULT_PLACEMENT = 'point-sample';
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/**
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* Returns a template function (function that accepts template parameters and returns a string)
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* to generate an aggregation query.
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* Valid options to define the query template are:
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* - placement
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* - columns
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* - dimensions*
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* The query template parameters taken by the result template function are:
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* - sourceQuery
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* - res
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* - columns
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* - dimensions
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*/
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const templateForOptions = (options) => {
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let templateFn = defaultAggregationQueryTemplate;
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if (!options.isDefaultAggregation) {
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templateFn = aggregationQueryTemplates[options.placement || DEFAULT_PLACEMENT];
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if (!templateFn) {
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throw new Error("Invalid Aggregation placement: '" + options.placement + "'");
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}
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}
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return templateFn;
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};
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/**
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* Generates an aggregation query given the aggregation options:
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* - query
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* - resolution - defined as in torque:
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* aggregation cell is resolution*resolution pixels, where tiles are always 256x256 pixels
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* - columns
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* - placement
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* - dimensions
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*
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* The default aggregation (when no explicit placement, columns or dimensions are present) returns
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* a sample record (with all the original columns and _cdb_feature_count) for each aggregation group.
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* When placement, columns or dimensions are specified, columns are aggregated as requested
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* (by default only _cdb_feature_count) and with the_geom_webmercator as defined by placement.
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*/
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const queryForOptions = (options) => templateForOptions(options)({
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sourceQuery: options.query,
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res: 256/options.resolution,
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columns: options.columns,
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dimensions: options.dimensions,
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filters: options.filters
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});
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module.exports = queryForOptions;
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const SUPPORTED_AGGREGATE_FUNCTIONS = {
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'count': {
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sql: (column_name, params) => `count(${params.aggregated_column || '*'})`
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},
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'avg': {
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sql: (column_name, params) => `avg(${params.aggregated_column || column_name})`
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},
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'sum': {
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sql: (column_name, params) => `sum(${params.aggregated_column || column_name})`
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},
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'min': {
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sql: (column_name, params) => `min(${params.aggregated_column || column_name})`
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},
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'max': {
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sql: (column_name, params) => `max(${params.aggregated_column || column_name})`
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},
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'mode': {
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sql: (column_name, params) => `_cdb_mode(${params.aggregated_column || column_name})`
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}
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};
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module.exports.SUPPORTED_AGGREGATE_FUNCTIONS = Object.keys(SUPPORTED_AGGREGATE_FUNCTIONS);
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const sep = (list) => {
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let expr = list.join(', ');
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return expr ? ', ' + expr : expr;
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};
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const aggregateColumns = ctx => {
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return Object.assign({
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_cdb_feature_count: {
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aggregate_function: 'count'
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}
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}, ctx.columns || {});
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};
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const aggregateColumnNames = (ctx, table) => {
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let columns = aggregateColumns(ctx);
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if (table) {
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return sep(Object.keys(columns).map(
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column_name => `${table}.${column_name}`
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));
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}
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return sep(Object.keys(columns));
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};
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const aggregateExpression = (column_name, column_parameters) => {
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const aggregate_function = column_parameters.aggregate_function || 'count';
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const aggregate_definition = SUPPORTED_AGGREGATE_FUNCTIONS[aggregate_function];
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if (!aggregate_definition) {
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throw new Error("Invalid Aggregate function: '" + aggregate_function + "'");
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}
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return aggregate_definition.sql(column_name, column_parameters);
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};
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const aggregateColumnDefs = ctx => {
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let columns = aggregateColumns(ctx);
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return sep(Object.keys(columns).map(column_name => {
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const aggregate_expression = aggregateExpression(column_name, columns[column_name]);
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return `${aggregate_expression} AS ${column_name}`;
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}));
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};
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const aggregateDimensions = ctx => ctx.dimensions || {};
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const dimensionNames = (ctx, table) => {
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let dimensions = aggregateDimensions(ctx);
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if (table) {
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return sep(Object.keys(dimensions).map(
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dimension_name => `${table}.${dimension_name}`
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));
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}
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return sep(Object.keys(dimensions));
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};
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const dimensionDefs = ctx => {
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let dimensions = aggregateDimensions(ctx);
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return sep(Object.keys(dimensions).map(dimension_name => {
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const expression = dimensions[dimension_name];
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return `${expression} AS ${dimension_name}`;
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}));
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};
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const aggregateFilters = ctx => ctx.filters || {};
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const filterConditionSQL = (expr, filter) => {
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// TODO: validate filter parameters (e.g. cannot have both greater_than and greater_than or equal to)
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if (filter) {
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if (!Array.isArray(filter)) {
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filter = [filter];
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}
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if (filter.length > 0) {
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return filter.map(f => filterSingleConditionSQL(expr, f)).join(' OR ');
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}
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}
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};
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const filterSingleConditionSQL = (expr, filter) => {
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let cond;
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Object.keys(FILTERS).some(f => {
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cond = FILTERS[f](expr, filter);
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return cond;
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});
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return cond;
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};
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const sqlQ = (value) => {
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if (isFinite(value)) {
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return String(value);
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}
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return `'${value}'`; // TODO: escape single quotes! (by doubling them)
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};
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/* jshint eqeqeq: false */
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/* x != null is used to check for both null and undefined; triple !== wouldn't do the trick */
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const FILTERS = {
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between: (expr, filter) => {
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const lo = filter.greater_than_or_equal_to, hi = filter.less_than_or_equal_to;
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if (lo != null && hi != null) {
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return `(${expr} BETWEEN ${sqlQ(lo)} AND ${sqlQ(hi)})`;
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}
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},
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in: (expr, filter) => {
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if (filter.in != null) {
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return `(${expr} IN (${filter.in.map(v => sqlQ(v)).join(',')}))`;
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}
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},
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notin: (expr, filter) => {
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if (filter.not_in != null) {
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return `(${expr} NOT IN (${filter.not_in.map(v => sqlQ(v)).join(',')}))`;
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}
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},
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equal: (expr, filter) => {
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if (filter.equal != null) {
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return `(${expr} = ${sqlQ(filter.equal)})`;
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}
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},
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not_equal: (expr, filter) => {
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if (filter.not_equal != null) {
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return `(${expr} <> ${sqlQ(filter.not_equal)})`;
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}
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},
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range: (expr, filter) => {
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let conds = [];
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if (filter.greater_than_or_equal_to != null) {
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conds.push(`(${expr} >= ${sqlQ(filter.greater_than_or_equal_to)})`);
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}
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if (filter.greater_than != null) {
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conds.push(`(${expr} > ${sqlQ(filter.greater_than)})`);
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}
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if (filter.less_than_or_equal_to != null) {
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conds.push(`(${expr} <= ${sqlQ(filter.less_than_or_equal_to)})`);
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}
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if (filter.less_than != null) {
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conds.push(`(${expr} < ${sqlQ(filter.less_than)})`);
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}
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if (conds.length > 0) {
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return conds.join(' AND ');
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}
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}
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};
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const filterConditions = ctx => {
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let columns = aggregateColumns(ctx);
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let dimensions = aggregateDimensions(ctx);
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let filters = aggregateFilters(ctx);
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return Object.keys(filters).map(filtered_column => {
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let filtered_expr;
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if (columns[filtered_column]) {
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filtered_expr = aggregateExpression(filtered_column, columns[filtered_column]);
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}
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else if (dimensions[filtered_column]) {
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filtered_expr = dimensions[filtered_column];
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}
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if (!filtered_expr) {
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throw new Error("Invalid filtered column: '" + filtered_column + "'");
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}
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return filterConditionSQL(filtered_expr, filters[filtered_column]);
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}).join(' AND ');
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};
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const havingClause = ctx => {
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let cond = filterConditions(ctx);
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return cond ? `HAVING ${cond}` : '';
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};
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// SQL expression to compute the aggregation resolution (grid cell size).
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// This is defined by the ctx.res parameter, which is the number of grid cells per tile linear dimension
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// (i.e. each tile is divided into ctx.res*ctx.res cells).
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// We limit the the minimum resolution to avoid division by zero problems. The limit used is
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// the pixel size of zoom level 30 (i.e. 1/2*(30+8) of the full earth web-mercator extent), which is about 0.15 mm.
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// Computing this using !scale_denominator!, !pixel_width! or !pixel_height! produces
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// inaccurate results due to rounding present in those values.
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const gridResolution = ctx => {
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const minimumResolution = 2*Math.PI*6378137/Math.pow(2,38);
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return `GREATEST(${256/ctx.res}*CDB_XYZ_Resolution(CDB_ZoomFromScale(!scale_denominator!)), ${minimumResolution})::double precision`;
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};
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// Notes:
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// * We need to filter spatially using !bbox! to make the queries efficient because
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// the filter added by Mapnik (wrapping the query)
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// is only applied after the aggregation.
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// * This queries are used for rendering and the_geom is omitted in the results for better performance
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// The special default aggregation includes all the columns of a sample row per grid cell and
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// the count (_cdb_feature_count) of the aggregated rows.
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const defaultAggregationQueryTemplate = ctx => `
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WITH
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_cdb_params AS (
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SELECT
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${gridResolution(ctx)} AS res,
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!bbox! AS bbox
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),
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_cdb_clusters AS (
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SELECT
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MIN(cartodb_id) AS cartodb_id
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${dimensionDefs(ctx)}
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${aggregateColumnDefs(ctx)}
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FROM (${ctx.sourceQuery}) _cdb_query, _cdb_params
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WHERE _cdb_query.the_geom_webmercator && _cdb_params.bbox
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GROUP BY
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Floor(ST_X(_cdb_query.the_geom_webmercator)/_cdb_params.res),
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Floor(ST_Y(_cdb_query.the_geom_webmercator)/_cdb_params.res)
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${dimensionNames(ctx)}
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) SELECT
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_cdb_query.*
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${aggregateColumnNames(ctx)}
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FROM
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_cdb_clusters INNER JOIN (${ctx.sourceQuery}) _cdb_query
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ON (_cdb_clusters.cartodb_id = _cdb_query.cartodb_id)
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`;
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const aggregationQueryTemplates = {
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'centroid': ctx => `
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WITH
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_cdb_params AS (
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SELECT
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${gridResolution(ctx)} AS res,
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!bbox! AS bbox
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)
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SELECT
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MIN(_cdb_query.cartodb_id) AS cartodb_id,
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ST_SetSRID(
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ST_MakePoint(
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AVG(ST_X(_cdb_query.the_geom_webmercator)),
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AVG(ST_Y(_cdb_query.the_geom_webmercator))
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), 3857
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) AS the_geom_webmercator
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${dimensionDefs(ctx)}
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${aggregateColumnDefs(ctx)}
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FROM (${ctx.sourceQuery}) _cdb_query, _cdb_params
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WHERE _cdb_query.the_geom_webmercator && _cdb_params.bbox
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GROUP BY
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Floor(ST_X(_cdb_query.the_geom_webmercator)/_cdb_params.res),
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Floor(ST_Y(_cdb_query.the_geom_webmercator)/_cdb_params.res)
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${dimensionNames(ctx)}
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${havingClause(ctx)}
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`,
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'point-grid': ctx => `
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WITH
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_cdb_params AS (
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SELECT
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${gridResolution(ctx)} AS res,
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!bbox! AS bbox
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),
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_cdb_clusters AS (
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SELECT
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MIN(_cdb_query.cartodb_id) AS cartodb_id,
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Floor(ST_X(_cdb_query.the_geom_webmercator)/_cdb_params.res)::int AS _cdb_gx,
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Floor(ST_Y(_cdb_query.the_geom_webmercator)/_cdb_params.res)::int AS _cdb_gy
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${dimensionDefs(ctx)}
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${aggregateColumnDefs(ctx)}
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FROM (${ctx.sourceQuery}) _cdb_query, _cdb_params
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WHERE the_geom_webmercator && _cdb_params.bbox
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GROUP BY _cdb_gx, _cdb_gy ${dimensionNames(ctx)}
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${havingClause(ctx)}
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)
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SELECT
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_cdb_clusters.cartodb_id AS cartodb_id,
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ST_SetSRID(ST_MakePoint((_cdb_gx+0.5)*res, (_cdb_gy+0.5)*res), 3857) AS the_geom_webmercator
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${dimensionNames(ctx)}
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${aggregateColumnNames(ctx)}
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FROM _cdb_clusters, _cdb_params
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`,
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'point-sample': ctx => `
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WITH
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_cdb_params AS (
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SELECT
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${gridResolution(ctx)} AS res,
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!bbox! AS bbox
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),
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_cdb_clusters AS (
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SELECT
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MIN(cartodb_id) AS cartodb_id
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${dimensionDefs(ctx)}
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${aggregateColumnDefs(ctx)}
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FROM (${ctx.sourceQuery}) _cdb_query, _cdb_params
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WHERE _cdb_query.the_geom_webmercator && _cdb_params.bbox
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GROUP BY
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Floor(ST_X(_cdb_query.the_geom_webmercator)/_cdb_params.res),
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Floor(ST_Y(_cdb_query.the_geom_webmercator)/_cdb_params.res)
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${dimensionNames(ctx)}
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${havingClause(ctx)}
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)
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SELECT
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_cdb_clusters.cartodb_id,
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the_geom, the_geom_webmercator
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${dimensionNames(ctx, '_cdb_clusters')}
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${aggregateColumnNames(ctx, '_cdb_clusters')}
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FROM
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_cdb_clusters INNER JOIN (${ctx.sourceQuery}) _cdb_query
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ON (_cdb_clusters.cartodb_id = _cdb_query.cartodb_id)
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`
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};
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module.exports.SUPPORTED_PLACEMENTS = Object.keys(aggregationQueryTemplates);
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module.exports.GEOMETRY_COLUMN = 'the_geom_webmercator';
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