在BigQuery + Angular + Firebase Functions中，由于BigQuery具有超大尺寸限制，当查询结果超过限制时，可以采取以下解决方法之一：

1. 分页查询：将查询结果分为多个较小的页面，使用BigQuery的limit和offset参数来限制每个页面的大小。在Angular中，可以使用分页组件来处理分页逻辑，并通过Firebase Functions来执行不同页面的查询。

// Angular Component

import { Component } from '@angular/core';
import { AngularFireFunctions } from '@angular/fire/functions';

@Component({
  selector: 'app-results',
  templateUrl: './results.component.html',
  styleUrls: ['./results.component.css']
})
export class ResultsComponent {
  currentPage: number = 1;
  pageSize: number = 10;
  totalResults: number = 0;
  results: any[] = [];

  constructor(private functions: AngularFireFunctions) {}

  ngOnInit() {
    this.loadResults();
  }

  loadResults() {
    const query = this.functions.httpsCallable('queryBigQuery');
    query({ page: this.currentPage, pageSize: this.pageSize }).subscribe(
      (response: any) => {
        this.totalResults = response.totalResults;
        this.results = response.results;
      },
      (error: any) => {
        console.error(error);
      }
    );
  }

  nextPage() {
    this.currentPage++;
    this.loadResults();
  }

  previousPage() {
    this.currentPage--;
    this.loadResults();
  }
}

// Firebase Functions

const { BigQuery } = require('@google-cloud/bigquery');

exports.queryBigQuery = functions.https.onCall(async (data, context) => {
  const page = data.page || 1;
  const pageSize = data.pageSize || 10;

  const bigquery = new BigQuery();
  const query = `SELECT * FROM myTable LIMIT ${pageSize} OFFSET ${(page - 1) * pageSize}`;
  const options = {
    query: query,
    location: 'US',
  };

  const [rows] = await bigquery.query(options);

  const totalResults = rows.length; // Total results for pagination
  const results = rows.map(row => row); // Modify this based on your actual results structure

  return {
    totalResults: totalResults,
    results: results
  };
});

2. 使用BigQuery导出功能：如果查询结果非常庞大，无法通过分页查询来处理，可以考虑使用BigQuery的导出功能，将查询结果导出到Google Cloud Storage（GCS）中。然后，可以使用Angular和Firebase Functions从GCS读取导出的文件并进行处理。

// Angular Component

import { Component } from '@angular/core';
import { AngularFireStorage } from '@angular/fire/storage';
import { AngularFireFunctions } from '@angular/fire/functions';

@Component({
  selector: 'app-results',
  templateUrl: './results.component.html',
  styleUrls: ['./results.component.css']
})
export class ResultsComponent {
  downloadUrl: string = '';
  loading: boolean = false;

  constructor(private storage: AngularFireStorage, private functions: AngularFireFunctions) {}

  ngOnInit() {
    this.executeQuery();
  }

  executeQuery() {
    const query = this.functions.httpsCallable('executeBigQuery');
    query({}).subscribe(
      (response: any) => {
        this.downloadUrl = response.downloadUrl;
      },
      (error: any) => {
        console.error(error);
      }
    );
  }

  downloadResults() {
    this.loading = true;

    const ref = this.storage.refFromURL(this.downloadUrl);
    ref.getDownloadURL().subscribe(
      (url: string) => {
        window.open(url, '_blank');
        this.loading = false;
      },
      (error: any) => {
        console.error(error);
        this.loading = false;
      }
    );
  }
}

// Firebase Functions

const { BigQuery } = require('@google-cloud/bigquery');

exports.executeBigQuery = functions.https.onCall(async (data, context) => {
  const bigquery = new BigQuery();
  const query = `SELECT * FROM myTable`;
  const options = {
    query: query,
    location: 'US',
  };

  const [job] = await bigquery.createQueryJob(options);

  // Wait for the job to complete
  await job.getQueryResults();

  const [files] = await job.getQueryResults({ destinationFormat: 'CSV', gzip: true });
  const [file] = files;

  const bucketName = file.metadata.bucket;
  const fileName = file.metadata.name;
  const downloadUrl = `https://