Algolia Firestore Sync库可以很容易地将Firebase Cloud Firestore中的数据同步到Algolia搜索引擎中，以便快速搜索和发现。但是，当数据集非常大且更改频繁时，会出现同步问题。解决方法是使用Cloud Functions和batchWrites来限制同步速率，并在随后的同步迭代中处理剩余的数据。下面是这个过程的代码示例：

const admin = require('firebase-admin');
const algoliasearch = require('algoliasearch');

admin.initializeApp();
const firestore = admin.firestore();
const algolia = algoliasearch(ALGOLIA_APP_ID, ALGOLIA_ADMIN_API_KEY, {timeout: 60000});

exports.syncAlgoliaWithFirestore = functions.firestore.document('collection/{docId}').onWrite((change, context) => {
  // Throttle sync functionality to prevent exceeding Algolia's rate limits
  const syncCount = writeCount.increment();
  console.log(`Syncing ${context.params.docId}`);

  if (syncCount % BATCH_SIZE !== 0) {
    console.log(`Skipping sync for ${context.params.docId}`);
    return null;
  }

  // Perform a batch write of Firestore records to Algolia
  const collectionIndex = algolia.initIndex('collection');
  const querySnapshot = await firestore.collection('collection').get();
  const records = querySnapshot.docs.map((doc) => {
    const data = doc.data();
    data.objectID = doc.id;
    return data;
  });

  try {
    await collectionIndex.saveObjects(records);
    console.log(`Sync successful for ${context.params.docId}`);
  } catch (error) {
    console.error(`Error syncing ${context.params.docId}`, error);
  }

  return null;
});

此函数使用batchWrites来限制每个同步到Algolia的记录数。例如，在此示例中，我们每隔100条记录同步一次。此外，我们使用Cloud Functions监视我们的Firestore集合，并在更改时启动同步函数。最后，我们从Firestore中获取记录并