#### Connection Timeouts
```java
// Increase timeout values
client.setConnectionTimeout(60000);  // 60 seconds
client.setSocketTimeout(120000);     // 120 seconds
```

#### Memory Issues
```java
// Reduce concurrent threads and batch sizes
crawler.crawlerContext.setNumOfThread(5);
crawler.crawlerContext.setMaxAccessCount(1000);
```

#### SSL/TLS Issues
```java
// Configure SSL settings

	},
	ErrSlowDownRead: {
		Code:           "SlowDownRead",
		Description:    "Resource requested is unreadable, please reduce your request rate",
		HTTPStatusCode: http.StatusServiceUnavailable,
	},
	ErrSlowDownWrite: {
		Code:           "SlowDownWrite",
		Description:    "Resource requested is unwritable, please reduce your request rate",
		HTTPStatusCode: http.StatusServiceUnavailable,
	},
	ErrMaxVersionsExceeded: {

   * HashSet}, will produce non-deterministic results.
   *
   * <p><b>Java 8+ users:</b> Use a chain of calls to {@link Comparator#thenComparing(Comparator)},
   * or {@code comparatorCollection.stream().reduce(Comparator::thenComparing).get()} (if the
   * collection might be empty, also provide a default comparator as the {@code identity} parameter
   * to {@code reduce}).
   *

	// if disk max timeout is smaller than checkEvery window
	// reduce checks by a second.
	if globalDriveConfig.GetMaxTimeout() <= checkEvery {
		checkEvery = globalDriveConfig.GetMaxTimeout() - time.Second
		if checkEvery <= 0 {
			checkEvery = globalDriveConfig.GetMaxTimeout()
		}
	}

	// if disk max timeout is smaller than skipIfSuccessBefore window
	// reduce the skipIfSuccessBefore by a second.

lock {\n  width: 100%;\n}\n\n.fade {\n  transition: opacity 0.15s linear;\n}\n\n@media (prefers-reduced-motion: reduce) {\n  .fade {\n    transition: none;\n  }\n}\n\n.fade:not(.show) {\n  opacity: 0;\n}\n\n.collapse:not(.show) {\n  display: none;\n}\n\n.collapsing {\n  position: relative;\n  height: 0;\n  overflow: hidden;\n  transition: height 0.35s ease;\n}\n\n@media (prefers-reduced-motion: reduce) {\n  .collapsing {\n    transition: none;\n  }\n}\n\n.collapsing.width {\n  width: 0;\n  height:...

   * Returns a new immutable array containing the values in the specified range.
   *
   * <p><b>Performance note:</b> The returned array has the same full memory footprint as this one
   * does (no actual copying is performed). To reduce memory usage, use {@code subArray(start,
   * end).trimmed()}.
   */
  public ImmutableLongArray subArray(int startIndex, int endIndex) {
    Preconditions.checkPositionIndexes(startIndex, endIndex, length());

   * Returns a new immutable array containing the values in the specified range.
   *
   * <p><b>Performance note:</b> The returned array has the same full memory footprint as this one
   * does (no actual copying is performed). To reduce memory usage, use {@code subArray(start,
   * end).trimmed()}.
   */
  public ImmutableIntArray subArray(int startIndex, int endIndex) {
    Preconditions.checkPositionIndexes(startIndex, endIndex, length());

    @SuppressWarnings("SynchronizeOnNonFinalField")
    public T get() {
      // Another variant of Double Checked Locking.
      //
      // We use two volatile reads. We could reduce this to one by
      // putting our fields into a holder class, but (at least on x86)
      // the extra memory consumption and indirection are more
      // expensive than the extra volatile reads.

        and `tf.data.Dataset.with_options()` respectively.
    *   New `tf.data.Dataset.reduce()` API allows users to reduce a finite
        dataset to a single element using a user-provided reduce function.
    *   New `tf.data.Dataset.window()` API allows users to create finite windows
        of input dataset; when combined with the `tf.data.Dataset.reduce()` API,
        this allows users to implement customized batching.

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