labels.labelTypeIds=Etichette
labels.lang=Lingua
labels.outputs=Output
labels.pos=Parte del discorso
labels.purgeJobLogDay=Elimina log di lavoro precedenti
labels.purgeUserInfoDay=Elimina log utente precedenti
labels.reading=Lettura
labels.roleTypeIds=ID ruolo
labels.scriptData=Script
labels.scriptResult=Risultato
labels.scriptType=Tipo di esecuzione
labels.segmentation=Segmentazione
labels.startTime=Ora di inizio

	if err != nil {
		return PartInfo{}, err
	}

	ctx = plkctx.Context()
	defer partIDLock.Unlock(plkctx)

	// Read lock for upload id, only held while reading the upload metadata.
	uploadIDRLock := er.NewNSLock(bucket, pathJoin(object, uploadID))
	rlkctx, err := uploadIDRLock.GetRLock(ctx, globalOperationTimeout)
	if err != nil {
		return PartInfo{}, err
	}

      /*
       * requireNonNull is safe because we accepted an Iterable of non-null Future instances, and we
       * don't overwrite an element in the array until after reading it.
       */
      ListenableFuture<? extends T> inputFuture = requireNonNull(inputFutures[inputFutureIndex]);
      // Null out our reference to this future, so it can be GCed

labels.jobLogging=日志记录
labels.jobName=名称
labels.jobStatus=状态
labels.labelTypeIds=标签
labels.lang=语言
labels.outputs=输出
labels.pos=词性
labels.purgeJobLogDay=删除以前的作业日志
labels.purgeUserInfoDay=删除以前的用户日志
labels.reading=阅读
labels.roleTypeIds=角色ID
labels.scriptData=脚本
labels.scriptResult=结果
labels.scriptType=执行方法
labels.segmentation=分段
labels.startTime=开始时间
labels.target=目标
labels.token=令牌
labels.synonymFile=同义词文件

	// is too large we are basically just thrashing the CPU D-cache.
	// So if the result length is larger than an empirically-found
	// limit (8KB), we stop growing the source string once the limit
	// is reached and keep reusing the same source string - that
	// should therefore be always resident in the L1 cache - until we
	// have completed the construction of the result.
	// This yields significant speedups (up to +100%) in cases where

- DRA BindingConditions: when the DRABindingConditions feature was enabled, reusing the same claim among different pods may have caused a panic in the scheduler when deallocation happens in parallel (a rare race condition). ([#137371](https://github.com/kubernetes/kubernetes/pull/137371), [@pohly](https://github.com/pohly)) [SIG...

    val response = call.execute()
    val inputStream = response.body.byteStream()
    assertThat(inputStream.read().toChar()).isEqualTo('A')
    call.cancel()
    assertFailsWith<IOException> {
      // Reading 'B' may succeed if it's buffered.
      inputStream.read()

      // But 'C' shouldn't be buffered (the response is throttled) and this should fail.
      inputStream.read()
    }
    inputStream.close()

-medium-m:before{content:"\f3c7"}.fa-medkit:before{content:"\f0fa"}.fa-medrt:before{content:"\f3c8"}.fa-meetup:before{content:"\f2e0"}.fa-megaport:before{content:"\f5a3"}.fa-meh:before{content:"\f11a"}.fa-meh-blank:before{content:"\f5a4"}.fa-meh-rolling-eyes:before{content:"\f5a5"}.fa-memory:before{content:"\f538"}.fa-mendeley:before{content:"\f7b3"}.fa-menorah:before{content:"\f676"}.fa-mercury:before{content:"\f223"}.fa-meteor:before{content:"\f753"}.fa-microblog:before{content:"\f91a"}.fa-mic...

### kubectl rolling-update: < v1.4.0 client vs >=v1.4.0 cluster

Old version kubectl's rolling-update command is compatible with Kubernetes 1.4 and higher only if you specify a new replication controller name. You will need to update to kubectl 1.4 or higher to use the rolling update command against a 1.4 cluster if you want to keep the original name, or you'll have to do two rolling updates.

labels.jobLogging=ロギング
labels.jobName=名前
labels.jobStatus=状態
labels.labelTypeIds=ラベル
labels.lang=言語
labels.outputs=対象
labels.pos=品詞
labels.purgeJobLogDay=以前のジョブログを削除
labels.purgeUserInfoDay=以前のユーザーログを削除
labels.reading=読み
labels.roleTypeIds=ロールID
labels.scriptData=スクリプト
labels.scriptResult=結果
labels.scriptType=実行方法
labels.segmentation=分割
labels.startTime=開始時間
labels.target=対象
labels.token=トークン