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benchmarks/src/main/java/org/elasticsearch/benchmark/search/fetch/subphase/FetchSourcePhaseBenchmark.java
sourceBytes = read300BytesExample(); break; case "one_4k_field": sourceBytes = buildBigExample("huge".repeat(1024)); break; case "one_4m_field": sourceBytes = buildBigExample("huge".repeat(1024 * 1024)); break; default: throw new IllegalArgumentException("Unknown source [" + source + "]");
Created: Wed Apr 08 16:19:15 GMT 2026 - Last Modified: Mon Sep 13 17:34:14 GMT 2021 - 5.4K bytes - Click Count (0) -
docs/orchestration/README.md
container based compute environment. A cloud-native application is portable and resilient by design, and can scale horizontally by simply replicating. Modern orchestration platforms like Kubernetes, DC/OS make replicating and managing containers in huge clusters easier than ever. While containers provide isolated application execution environment, orchestration platforms allow seamless scaling by helping replicate and manage containers. MinIO extends this by adding isolated storage environment...
Created: Sun Apr 05 19:28:12 GMT 2026 - Last Modified: Tue Aug 12 18:20:36 GMT 2025 - 2.2K bytes - Click Count (0) -
doc/godebug.md
This setting will be removed in Go 1.27. Go 1.22 changed how the runtime interacts with transparent huge pages on Linux. In particular, a common default Linux kernel configuration can result in significant memory overheads, and Go 1.22 no longer works around this default. To work around this issue without adjusting kernel settings, transparent huge pages can be disabled for Go memory with the
Created: Tue Apr 07 11:13:11 GMT 2026 - Last Modified: Fri Mar 20 15:49:10 GMT 2026 - 26K bytes - Click Count (0) -
android/guava/src/com/google/common/cache/Striped64.java
* scattered in memory and thus don't interfere much with each * other. But Atomic objects residing in arrays will tend to be * placed adjacent to each other, and so will most often share * cache lines (with a huge negative performance impact) without * this precaution. * * In part because Cells are relatively large, we avoid creating * them until they are needed. When there is no contention, all
Created: Fri Apr 03 12:43:13 GMT 2026 - Last Modified: Wed Jan 15 22:17:15 GMT 2025 - 11.4K bytes - Click Count (0) -
src/archive/zip/zip_test.go
// 0xFFFFFFFF, but not before. func TestZip64DirectoryOffset(t *testing.T) { if testing.Short() { t.Skip("skipping in short mode") } t.Parallel() const filename = "huge.txt" gen := func(wantOff uint64) func(*Writer) { return func(w *Writer) { w.testHookCloseSizeOffset = func(size, off uint64) { if off != wantOff {
Created: Tue Apr 07 11:13:11 GMT 2026 - Last Modified: Thu May 23 01:00:11 GMT 2024 - 19.6K bytes - Click Count (0) -
android/guava/src/com/google/common/hash/Striped64.java
* scattered in memory and thus don't interfere much with each * other. But Atomic objects residing in arrays will tend to be * placed adjacent to each other, and so will most often share * cache lines (with a huge negative performance impact) without * this precaution. * * In part because Cells are relatively large, we avoid creating * them until they are needed. When there is no contention, all
Created: Fri Apr 03 12:43:13 GMT 2026 - Last Modified: Wed Jan 15 22:17:15 GMT 2025 - 11.4K bytes - Click Count (0) -
src/bufio/scan_test.go
s.Split(c.split) for s.Scan() { } if s.Err() != nil { t.Fatal("after scan:", s.Err()) } if c != 0 { t.Fatalf("stopped with %d left to process", c) } } // Make sure we can read a huge token if a big enough buffer is provided. func TestHugeBuffer(t *testing.T) { text := strings.Repeat("x", 2*MaxScanTokenSize) s := NewScanner(strings.NewReader(text + "\n")) s.Buffer(make([]byte, 100), 3*MaxScanTokenSize)
Created: Tue Apr 07 11:13:11 GMT 2026 - Last Modified: Fri Sep 22 16:22:42 GMT 2023 - 14.3K bytes - Click Count (0) -
docs/en/docs/async.md
* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time. * **Deep Learning**: this is a sub-field of Machine Learning, so, the same applies. It's just that there is not a single spreadsheet of numbers to multiply, but a huge set of them, and in many cases, you use a special processor to build and / or use those models.
Created: Sun Apr 05 07:19:11 GMT 2026 - Last Modified: Thu Mar 05 18:13:19 GMT 2026 - 23.4K bytes - Click Count (0) -
src/test/java/jcifs/internal/dtyp/SecurityDescriptorTest.java
@ValueSource(ints = { 0, 1, 10, 100, 1000, 4096 }) void testDecodeWithVariousAceCounts(int aceCount) throws SMBProtocolDecodingException { // This test is theoretical as we can't create huge buffers // but tests the boundary conditions if (aceCount <= 10) { // Only test small counts practically byte[] buffer = new byte[2048];Created: Sun Apr 05 00:10:12 GMT 2026 - Last Modified: Thu Aug 14 05:31:44 GMT 2025 - 18.6K bytes - Click Count (0) -
android/guava/src/com/google/common/util/concurrent/Striped.java
* lock.unlock(); * } * * If we only held the int[] stripes, translating it on the fly to L's, the original locks might * be garbage collected after locking them, ending up in a huge mess. */ @SuppressWarnings("unchecked") // we carefully replaced all keys with their respective L's List<L> asStripes = (List<L>) result; return Collections.unmodifiableList(asStripes); }
Created: Fri Apr 03 12:43:13 GMT 2026 - Last Modified: Tue Sep 16 22:01:32 GMT 2025 - 20.6K bytes - Click Count (0)