How do you combine virtualization with data search and filtering?

To effectively combine virtualization (virtual scroll) with data searching and filtering on the frontend, several points should be considered:

1. Filtering and searching should work on the full dataset, not just the visible part. Usually, this means filtering occurs before virtualization.

2. After applying filters and search, a new data array is formed, which is passed to the virtualization component.

3. Virtualization renders only the visible elements from this filtered array, which helps save resources when dealing with large amounts of data.

Example in React using react-window:

import { FixedSizeList as List } from 'react-window';
import { useState, useMemo } from 'react';

function FilteredVirtualList({ items }) {
  const [query, setQuery] = useState('');

  const filteredItems = useMemo(() => {
    return items.filter(item => item.name.includes(query));
  }, [items, query]);

  return (
    <>
      <input value={query} onChange={e => setQuery(e.target.value)} placeholder="Search" />
      <List
        height={400}
        itemCount={filteredItems.length}
        itemSize={35}
        width={300}
      >
        {({ index, style }) => (
          <div style={style}>{filteredItems[index].name}</div>
        )}
      </List>
    </>
  );
}

Thus, searching and filtering work on the full dataset, while virtualization ensures efficient rendering of only the visible part of the list.