forked from geolba/tethys.frontend
OpenSearch - some progress in migration
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@ -1,15 +1,34 @@
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import initializeAxios from "./axiosSetup";
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import { axiosRequestConfiguration } from "./config";
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import { map } from "rxjs/operators";
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import { defer, Observable } from "rxjs";
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import { AxiosResponse } from "axios";
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// https://ichi.pro/de/so-wickeln-sie-axios-mit-typescript-und-react-in-rxjs-ein-118892823169891
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// Import the necessary modules and functions
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import initializeAxios from "./axiosSetup"; // Function to initialize the Axios instance
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import { axiosRequestConfiguration } from "./config"; // Axios configuration settings
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import { map } from "rxjs/operators"; // Operator to transform the items emitted by an Observable
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import { defer, Observable } from "rxjs"; // RxJS utilities for creating and working with Observables
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import { AxiosResponse } from "axios"; // Axios response type
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// Initialize the Axios instance with the provided configuration
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const axiosInstance = initializeAxios(axiosRequestConfiguration);
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// Function to make a GET request using Axios wrapped in an Observable
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// eslint-disable-next-line
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const get = <T>(url: string, queryParams?: any): Observable<T> => {
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return defer(() => axiosInstance.get<T>(url, { params: queryParams })).pipe(map((result: AxiosResponse) => result.data));
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// Use defer to create an Observable that makes the Axios GET request when subscribed to
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return defer(() => axiosInstance.get<T>(url, { params: queryParams }))
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// Use map to transform the Axios response to extract the data property
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.pipe(map((result: AxiosResponse) => result.data));
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};
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export default { get };
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// Function to make a POST request using Axios wrapped in an Observable
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const post = <T>(url: string, body: any, queryParams?: any): Observable<T> => {
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// Use defer to create an Observable that makes the Axios POST request when subscribed to
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return defer(() => axiosInstance.post<T>(url, body, {
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params: queryParams,
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headers: {
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'Accept': 'application/json',
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'Content-Type': 'application/json'
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}
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}))
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.pipe(map((result: AxiosResponse) => result.data)); // Use map to transform the Axios response to extract the data property
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};
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// Export the get function as part of the default export
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export default { get, post };
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@ -88,7 +88,9 @@ export default class VsInput extends Vue {
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// };
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const suggestions = new Array<Suggestion>();
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console.log("Display:", this.display);
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console.log("Display:", this.display);
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// console.log("results:", this.results );
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this.results.forEach((dataset) => {
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@ -106,23 +108,23 @@ export default class VsInput extends Vue {
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suggestions.push(suggestion);
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}
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}
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if (this.find(dataset.author, this.display.toLowerCase()) !== "") {
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const author = this.find(dataset.author, this.display.toLowerCase());
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// if (this.find(dataset.author, this.display.toLowerCase()) !== "") {
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// const author = this.find(dataset.author, this.display.toLowerCase());
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const hasAuthorSuggestion = suggestions.some((suggestion) => suggestion.value === author && suggestion.type == SearchType.Author);
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if (!hasAuthorSuggestion) {
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const suggestion = new Suggestion(author, SearchType.Author);
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suggestions.push(suggestion);
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}
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}
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if (this.find(dataset.subject, this.display.toLowerCase()) != "") {
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const subject = this.find(dataset.subject, this.display.toLowerCase());
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const hasSubjectSuggestion = suggestions.some((suggestion) => suggestion.value === subject && suggestion.type == SearchType.Subject);
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if (!hasSubjectSuggestion) {
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const suggestion = new Suggestion(subject, SearchType.Subject);
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suggestions.push(suggestion);
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}
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}
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// const hasAuthorSuggestion = suggestions.some((suggestion) => suggestion.value === author && suggestion.type == SearchType.Author);
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// if (!hasAuthorSuggestion) {
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// const suggestion = new Suggestion(author, SearchType.Author);
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// suggestions.push(suggestion);
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// }
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// }
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// if (this.find(dataset.subject, this.display.toLowerCase()) != "") {
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// const subject = this.find(dataset.subject, this.display.toLowerCase());
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// const hasSubjectSuggestion = suggestions.some((suggestion) => suggestion.value === subject && suggestion.type == SearchType.Subject);
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// if (!hasSubjectSuggestion) {
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// const suggestion = new Suggestion(subject, SearchType.Subject);
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// suggestions.push(suggestion);
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// }
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// }
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});
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return suggestions;
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@ -174,7 +176,8 @@ export default class VsInput extends Vue {
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private request(): void {
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console.log("request()");
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DatasetService.searchTerm(this.display, this.solr.core, this.solr.host).subscribe({
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// DatasetService.searchTerm(this.display, this.solr.core, this.solr.host).subscribe({
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DatasetService.searchTerm(this.display).subscribe({
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next: (res: Dataset[]) => this.dataHandler(res),
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error: (error: string) => this.errorHandler(error),
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complete: () => (this.loading = false),
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@ -7,14 +7,6 @@ export interface SolrResponse {
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// facet_counts: FacetCount;
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}
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// OPENSEARCH
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export interface OpenResponse {
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responseHeader: ResponseHeader;
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response: ResponseContent;
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facets: FacetFields;
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// facet_counts: FacetCount;
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}
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export interface ResponseHeader {
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status: boolean;
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QTime: number;
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@ -79,3 +71,51 @@ export class FacetItem {
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}
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}
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//#endregion
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// OPENSEARCH
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// ========================================================================
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export interface OpenSearchResponse {
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took: number;
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timed_out: boolean;
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_shards: Shards;
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hits: Hits;
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aggregations?: Aggregations;
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}
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export interface Shards {
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total: number;
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successful: number;
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skipped: number;
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failed: number;
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}
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export interface Hits {
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total: Total;
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max_score: number;
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hits: Array<Hit>;
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}
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export interface Total {
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value: number;
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relation: string;
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}
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export interface Hit {
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_index: string;
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_id: string;
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_score: number;
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_source: Dataset;
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}
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export interface Aggregations {
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[key: string]: Aggregation;
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}
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export interface Aggregation {
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buckets: Array<Bucket>;
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}
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export interface Bucket {
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key: string;
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doc_count: number;
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}
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@ -3,44 +3,12 @@ import api from "../api/api";
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import { Observable } from "rxjs";
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import { map } from "rxjs/operators";
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import { Dataset, DbDataset, Suggestion } from "@/models/dataset";
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import { SolrResponse } from "@/models/headers";
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import { OpenSearchResponse, SolrResponse } from "@/models/headers";
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import { ActiveFilterCategories } from "@/models/solr";
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import { VUE_API } from "@/constants";
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import { deserialize } from "class-transformer";
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class DatasetService {
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// /* Initial test method to fetch and log data from the local OpenSearch endpoint (new backend) */
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// async fetchDataFromOpenSearch(searchTerm: string): Promise<void> {
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// const url = "http://192.168.21.18/tethys-records/_search";
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// const headers = {
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// "Content-Type": "application/json",
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// };
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// const body = {
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// query: {
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// match: {
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// title: searchTerm,
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// },
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// },
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// };
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// try {
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// const response = await fetch(url, {
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// method: "POST",
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// headers: headers,
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// body: JSON.stringify(body),
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// });
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// if (!response.ok) {
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// throw new Error(`Failed to fetch data from ${url}, status: ${response.status}`);
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// }
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// const data = await response.json();
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// console.log("Data from OpenSearch:", data);
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// } catch (error) {
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// console.error("Error fetching data:", error);
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// }
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// }
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/**
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* Fetch data from the OpenSearch endpoint with fuzzy search enabled.
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* This function allows for misspellings in the search term and boosts
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@ -50,7 +18,7 @@ class DatasetService {
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*/
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async fetchDataFromOpenSearch(searchTerm: string): Promise<void> {
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// Define the OpenSearch endpoint URL
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const url = "http://192.168.21.18/tethys-records/_search";
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const url = "http://opensearch.geoinformation.dev/tethys-records/_search";
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// Set the headers for the POST request
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const headers = {
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@ -149,68 +117,6 @@ class DatasetService {
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}
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};
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// // Construct the body of the POST request
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// const body = {
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// query: {
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// bool: {
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// // The `should` clause specifies that at least one of these conditions must match
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// should: [
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// {
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// // Match the search term in the title field with a wildcard
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// wildcard: {
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// title: {
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// value: `${searchTerm}*`, // Wildcard search for terms starting with searchTerm
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// boost: 3 // Boosting the relevance of title matches
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// }
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// }
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// },
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// {
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// // Match the search term in the author field with a wildcard
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// wildcard: {
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// author: {
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// value: `${searchTerm}*`, // Wildcard search for terms starting with searchTerm
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// boost: 2 // Boosting the relevance of author matches
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// }
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// }
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// },
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// {
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// // Match the search term in the subject field with a wildcard
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// wildcard: {
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// subject: {
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// value: `${searchTerm}*`, // Wildcard search for terms starting with searchTerm
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// boost: 1 // Boosting the relevance of subject matches
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// }
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// }
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// }
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// ],
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// // Ensure that at least one of the `should` clauses must match
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// minimum_should_match: 1
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// }
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// },
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// // Limit the number of search results to 10
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// size: 10,
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// // Start from the first result (pagination)
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// from: 0,
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// // Sort the results by the `server_date_published` field in descending order
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// sort: [
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// { server_date_published: { order: "desc" } }
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// ],
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// // Aggregations to provide facets for the `language` and `subject` fields
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// aggs: {
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// language: {
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// terms: {
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// field: "language.keyword" // Aggregate by the exact values of the `language` field
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// }
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// },
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// subject: {
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// terms: {
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// field: "subjects.keyword", // Aggregate by the exact values of the `subjects` field
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// size: 10 // Limit the number of aggregation buckets to 10
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// }
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// }
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// }
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// };
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try {
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// Send the POST request to the OpenSearch endpoint
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const response = await fetch(url, {
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terms%22%2C%20field%3A%20%22year%22%20%7D&json.facet.author=%7B%20type%3A%20%22terms%22%2C%20field%3A%20%22author_facet%22%2C%20limit%3A%20-1%20%7D
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*/
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private openSearchUrl = "http://opensearch.geoinformation.dev/tethys-records/_search";
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public searchTerm(term: string): Observable<Dataset[]> {
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const body = {
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query: {
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bool: {
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should: [
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{ match: { title: { query: term, fuzziness: "AUTO", boost: 3 } } },
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{ match: { author: { query: term, fuzziness: "AUTO", boost: 2 } } },
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{ match: { subject: { query: term, fuzziness: "AUTO", boost: 1 } } },
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{ wildcard: { title: { value: `${term}*`, boost: 3 } } },
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{ wildcard: { author: { value: `${term}*`, boost: 2 } } },
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{ wildcard: { subject: { value: `${term}*`, boost: 1 } } }
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],
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minimum_should_match: 1
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}
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},
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size: 10,
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from: 0,
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sort: [{ server_date_published: { order: "desc" } }],
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aggs: {
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language: { terms: { field: "language.keyword" } },
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subject: { terms: { field: "subjects.keyword", size: 10 } }
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}
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};
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return api.post<OpenSearchResponse>(this.openSearchUrl, body).pipe(
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map(response => response.hits.hits.map(hit => hit._source))
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);
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}
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// For the autocomplete search. Method to perform a search based on a term
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public searchTerm(term: string, solrCore: string, solrHost: string): Observable<Dataset[]> {
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public searchTerm_SOLR(term: string, solrCore: string, solrHost: string): Observable<Dataset[]> {
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// Calling the test method for
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this.fetchDataFromOpenSearch(term);
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// this.fetchDataFromOpenSearch(term);
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// solr endpoint
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const host = "https://" + solrHost;
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const path = "/solr/" + solrCore + "/select?";
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@ -276,6 +213,11 @@ class DatasetService {
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};
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// Make API call to Solr and return the result
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/**
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* When a GET request is made to the Solr server using the api.get<SolrResponse> method, the response received from Solr is an object that includes various details about the search results.
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* One of the key properties of this response object is docs, which is an array of documents (datasets) that match the search criteria.
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* It is used the pipe method to chain RxJS operators to the Observable returned by api.get. The map operator is used to transform the emitted items of the Observable.
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*/
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const stations = api.get<SolrResponse>(base, q_params).pipe(map((res: SolrResponse) => res.response.docs));
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return stations;
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@ -290,7 +232,9 @@ class DatasetService {
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&json.facet.year=%7B%20type%3A%20%22terms%22%2C%20field%3A%20%22year%22%20%7D
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&json.facet.author=%7B%20type%3A%20%22terms%22%2C%20field%3A%20%22author_facet%22%2C%20limit%3A%20-1%20%7D */
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// Method to perform a faceted search
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/**
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* This method performs a faceted search on a Solr core. Faceted search allows the user to filter search results based on various categories (facets)
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*/
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public facetedSearch(
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suggestion: Suggestion | string,
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activeFilterCategories: ActiveFilterCategories,
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@ -316,13 +260,13 @@ class DatasetService {
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"doctype",
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].toString();
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// Determine search term, query operator, and query fields based on the suggestion type
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// Determine search term, query operator, and query fields based on the suggestion type. Depending on whether suggestion is a string or a Suggestion object, it constructs the search term and query fields differently.
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let term, queryOperator, qfFields;
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if (typeof suggestion === "string") {
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if (typeof suggestion === "string") { // f suggestion is a string, it appends a wildcard (*) for partial matches.
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term = suggestion + "*";
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queryOperator = "or";
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qfFields = "title^3 author^2 subject^1";
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} else if (suggestion instanceof Suggestion) {
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} else if (suggestion instanceof Suggestion) { // If suggestion is a Suggestion object, it forms a more specific query based on the type and value of the suggestion.
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term = suggestion.type + ':"' + suggestion.value + '"';
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queryOperator = "and";
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qfFields = undefined;
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@ -10,7 +10,7 @@ import { OpenSettings } from "@/models/solr";
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import DatasetService from "../../services/dataset.service";
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import { Suggestion, Dataset, SearchType } from "@/models/dataset";
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// import { SolrResponse, FacetFields, FacetItem, FacetResults, FacetInstance } from "@/models/headers";
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import { OpenResponse, SolrResponse, FacetFields, FacetItem, FacetResults, FacetInstance } from "@/models/headers";
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import { SolrResponse, FacetFields, FacetItem, FacetResults, FacetInstance } from "@/models/headers";
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import { ActiveFilterCategories } from "@/models/solr";
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import { SOLR_HOST, SOLR_CORE } from "@/constants";
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import { IPagination } from "@/models/pagination";
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