final Map<String, Object> doc = new HashMap<>();
            doc.put("title", NAME_PREFIX + "large_" + i);
            doc.put("url", "http://example.com/bulk/large/" + i);
            doc.put("content", "This is test content for large bulk document " + i);
            doc.put("boost", 1.0f);
            doc.put("role", "Rguest");
            documents.add(doc);
        }

            if (fileSize > maxSize) {
                throw new IORuntimeException(new IOException(
                        "File too large: " + fileSize + " bytes (max: " + maxSize + " bytes). Use streaming APIs for large files."));
            }

            final ByteBuffer buffer = ByteBuffer.allocate((int) fileSize);
            ChannelUtil.read(channel, buffer);

        }
    }

    @Test
    public void test_execute_withVeryLargeBoost() {
        // Test executing BoostQuery with very large boost value
        Term term = new Term("field", "large");
        TermQuery termQuery = new TermQuery(term);
        BoostQuery boostQuery = new BoostQuery(termQuery, Float.MAX_VALUE);

        QueryContext context = new QueryContext("test", false);

from fastapi import FastAPI
from fastapi.responses import StreamingResponse

some_file_path = "large-video-file.mp4"
app = FastAPI()


@app.get("/")
def main():
    def iterfile():  # (1)
        with open(some_file_path, mode="rb") as file_like:  # (2)
            yield from file_like  # (3)

* It uses a "spooled" file:
    * A file stored in memory up to a maximum size limit, and after passing this limit it will be stored in disk.
* This means that it will work well for large files like images, videos, large binaries, etc. without consuming all the memory.
* You can get metadata from the uploaded file.
* It has a [file-like](https://docs.python.org/3/glossary.html#term-file-like-object) `async` interface.

from fastapi import FastAPI
from fastapi.responses import FileResponse

some_file_path = "large-video-file.mp4"
app = FastAPI()


@app.get("/")
async def main():

from fastapi import FastAPI
from fastapi.responses import FileResponse

some_file_path = "large-video-file.mp4"
app = FastAPI()


@app.get("/", response_class=FileResponse)
async def main():

  "durations" : [ {
    "testProject" : "excludeRuleMergingBuild",
    "linux" : 233
  } ]
}, {
  "scenario" : "org.gradle.performance.regression.corefeature.LargeDependencyGraphPerformanceTest.resolve large dependency graph (parallel = false, locking = true)",
  "durations" : [ {

   *       userspace buffer (byte[] or ByteBuffer), then copies them from that buffer into the
   *       destination channel.
   * </ol>
   *
   * This value is intended to be large enough to make the overhead of system calls negligible,
   * without being so large that it causes problems for systems with atypical memory management if
   * approaches 2 or 3 are used.
   */
  private static final int ZERO_COPY_CHUNK_SIZE = 512 * 1024;

* What test cases should it have? What could go wrong?
* How will it roughly be implemented? We'll happily provide code pointers to save you time.

We may ask you to answer these questions directly in the GitHub issue or (for large changes) in a shared Google Doc.

Please note that some features may be out of the team's current focus, and it can take significant time for the team to review the PR thoroughly and address it fully.

### Security vulnerabilities