}
    }
    connection.writePing()
    connection.shutdown(ErrorCode.PROTOCOL_ERROR)
    assertThat(connection.openStreamCount()).isEqualTo(1)
    connection.awaitPong() // Prevent the peer from exiting prematurely.

    // Verify the peer received what was expected.
    val synStream1 = peer.takeFrame()
    assertThat(synStream1.type).isEqualTo(Http2.TYPE_HEADERS)
    val pingFrame = peer.takeFrame()

                        dependency);
            }

            Dependency existing = index.get(key);

            if (existing != null) {
                String msg;
                if (equals(existing.getVersion(), dependency.getVersion())) {
                    msg = "duplicate declaration of version " + Objects.toString(dependency.getVersion(), "(?)");

We will now enable bucket event notifications on a bucket named `images`. Whenever a JPEG image is created/overwritten, a new document is added or an existing document is updated in the Elasticsearch index configured above. When an existing object is deleted, the corresponding document is deleted from the index. Thus, the rows in the Elasticsearch index, reflect the `.jpg` objects in the `images` bucket.

	x.versions = append(x.versions, xlMetaV2ShallowVersion{header: xlMetaV2VersionHeader{ModTime: -1}})

	// Linear search, we likely have to insert at front.
	for i, existing := range x.versions {
		if existing.header.ModTime <= modTime {
			// Insert at current idx. First move current back.
			copy(x.versions[i+1:], x.versions[i:])
			x.versions[i] = xlMetaV2ShallowVersion{
				header: ver.header(),

// -1 and `dims` can be null. If a dimension is unknown, the
// corresponding entry in the `dims` array must be -1.
//
// This does not overwrite the existing shape associated with `output`,
// but merges the input shape with the existing shape.  For example,
// setting a shape of [-1, 2] with an existing shape [2, -1] would set
// a final shape of [2, 2] based on shape merging semantics.
//
// Returns an error into `status` if:

#### ThirdPartyResource

If you use ThirdPartyResource objects, they have moved from being namespaced-scoped to be cluster-scoped. Before upgrading to 1.3.0, export and delete any existing ThirdPartyResource objects using a 1.2.x client:

kubectl get thirdpartyresource --all-namespaces -o yaml > tprs.yaml
kubectl delete -f tprs.yaml

                if (log.isTraceEnabled()) {
                    log.trace("Reusing existing session " + ssn);
                }
                return ssn.acquire();
            }
            if (log.isTraceEnabled()) {
                log.trace("Existing session " + ssn + " does not match " + tf.getCredentials());
            }
        }

        /* logoff old sessions */

	for _, fivs := range versionsMap {
		// Removal of existing versions and adding a delete marker in the same
		// request is supported. At the same time, we cannot allow adding
		// two delete markers on top of any object. To avoid this situation,
		// we will sort deletions to execute existing deletion first,
		// then add only one delete marker if requested

		cache.iamUserGroupMemberships = newCache.iamUserGroupMemberships
		cache.iamUserPolicyMap = newCache.iamUserPolicyMap
		cache.iamUsersMap = newCache.iamUsersMap
		// For STS policy map, we need to merge the new cache with the existing
		// cache because the periodic IAM reload is partial. The periodic load
		// here is to account for STS policy mapping changes that should apply
		// for service accounts derived from such STS accounts (i.e. LDAP STS

                }
              });
      thread.start();
      // we want to wait until each thread is WAITING - one thread waiting inside CacheLoader.load
      // (in startSignal.await()), and the others waiting for that thread's result.
      while (thread.isAlive() && thread.getState() != Thread.State.WAITING) {
        Thread.yield();
      }
    }
    gettersStartedSignal.countDown();
    gettersComplete.await();