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Minimizing Record Size

When you upload data to your index, its size will increase proportionally. To keep the index size manageable, HoppySearch recommends that you follow the steps below before indexing the data.

It is possible that you might not need to index every attribute of your data sources. Indexing everything will increase your record size, but you might not require all the data to build your search experience. Consider a scenario where you're developing an e-commerce website, and your dataset looks like the one below.

[
  {
  "product_name": "Samsung Galaxy M32",
  "category": "Mobiles",
  "brand": "Samsung",
  "price": 14999,
  "discount": 10,
  "description": "The Samsung Galaxy M32 comes with a stunning 6.4-inch Full HD+ Super AMOLED display, a powerful 6000mAh battery, and a versatile 64MP quad-camera setup.",
  "seller_name": "OmniTechRetail",
  "rating": 4.5,
  "num_ratings": 1000,
  "in_stock": true,
  "color": "Black",
  "storage_capacity": "128GB",
  "ram": null,
  "processor": "MediaTek Helio G80",
  "connectivity": "4G LTE"
  }
]

Suppose you only need "product_name," "category," "brand," "price," and "description" fields to search and display an item. In that case, you can remove all other fields to make the dataset smaller. The dataset will now look like below.

Benefits of the Above Process​

By following the above process of reducing record size before indexing data in HoppySearch, you can enjoy the following advantages:

  • Minimized index size: By removing unnecessary attributes, you can significantly reduce the size of your index, which can improve its performance and save you storage space.
  • Cleaner data: By eliminating irrelevant or redundant information from your records, you can make your data more accurate, consistent, and easier to manage.
  • More efficient search results: By focusing on the essential attributes that matter to your users, you can deliver more relevant and meaningful search results, which can enhance their search experience and satisfaction.