3.1 建立 redis-master Pod 及服務 我們可以先定義 Service，然後再定義一個 RC 來建立和控制相對應的 Pod，或者先 定義 RC 來建立 Pod，然後定義與其關聯的 Service，這兩種方式最終的結果都一 樣，這裡我們採用後面這種方式。 首 先 為 redis-master 服 務 建 立 一 個 名 為 redis-master 的 RC 定 義 檔：redis-master- 檔：redis-master- controller.yaml。下面提供該檔的完整內容： apiVersion: v1 kind: ReplicationController metadata: name: redis-master labels: name: redis-master spec: replicas: 1 selector: name: redis-master redis-master template: metadata: labels: name: redis-master 1-42 Kubernetes 入門 1 1.4.9 小結 上述這些元件是 Kubernetes 系統的核心元件，它們共同構成 Kubernetes 系統的框 架和運算模型。透過對它們進行靈活組合，使用者就可快速、方便地對容器叢集進 行配置、建置和管理。

disposal. julia> Threads.nthreads() 4 300CHAPTER 24. MULTI-THREADING 301 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you it's fairly obvious that a given CPU will have fastest access to the RAM within the same computer (node). Perhaps more surprisingly, similar issues are relevant on a typical multicore laptop, due to differences defaults to current user, port to the standard ssh port. count is the number of workers to spawn on the node, and defaults to 1. The optional bind-to bind_addr[:port] specifies the IP address and port that

disposal. julia> Threads.nthreads() 4 300CHAPTER 24. MULTI-THREADING 301 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you it's fairly obvious that a given CPU will have fastest access to the RAM within the same computer (node). Perhaps more surprisingly, similar issues are relevant on a typical multicore laptop, due to differences defaults to current user, port to the standard ssh port. count is the number of workers to spawn on the node, and defaults to 1. The optional bind-to bind_addr[:port] specifies the IP address and port that

disposal. 318CHAPTER 25. MULTI-THREADING 319 julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you it's fairly obvious that a given CPU will have fastest access to the RAM within the same computer (node). Perhaps more surprisingly, similar issues are relevant on a typical multicore laptop, due to differences defaults to current user, port to the standard ssh port. count is the number of workers to spawn on the node, and defaults to 1. The optional bind-to bind_addr[:port] specifies the IP address and port that

disposal. 318CHAPTER 25. MULTI-THREADING 319 julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you it's fairly obvious that a given CPU will have fastest access to the RAM within the same computer (node). Perhaps more surprisingly, similar issues are relevant on a typical multicore laptop, due to differences defaults to current user, port to the standard ssh port. count is the number of workers to spawn on the node, and defaults to 1. The optional bind-to bind_addr[:port] specifies the IP address and port that

disposal. 318CHAPTER 25. MULTI-THREADING 319 julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you it's fairly obvious that a given CPU will have fastest access to the RAM within the same computer (node). Perhaps more surprisingly, similar issues are relevant on a typical multicore laptop, due to differences defaults to current user, port to the standard ssh port. count is the number of workers to spawn on the node, and defaults to 1. The optional bind-to bind_addr[:port] specifies the IP address and port that

(_| | | Version 1.13.0-DEV.639 (2025-05-25) _/ |\__'_|_|_|\__'_| | Commit 925d504ade4 (1 day old master) |__/ | julia> 1 + 2 3 julia> ans 3 To exit the interactive session, type CTRL-D (press the verify there are 4 threads at our disposal. julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you it's fairly obvious that a given CPU will have fastest access to the RAM within the same computer (node). Perhaps more surprisingly, similar issues are relevant on a typical multicore laptop, due to differences

verify there are 4 threads at our disposal. julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you it's fairly obvious that a given CPU will have fastest access to the RAM within the same computer (node). Perhaps more surprisingly, similar issues are relevant on a typical multicore laptop, due to differences defaults to current user, port to the standard ssh port. count is the number of workers to spawn on the node, and defaults to 1. The optional bind-to bind_addr[:port] specifies the IP address and port that

verify there are 4 threads at our disposal. julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you it's fairly obvious that a given CPU will have fastest access to the RAM within the same computer (node). Perhaps more surprisingly, similar issues are relevant on a typical multicore laptop, due to differences defaults to current user, port to the standard ssh port. count is the number of workers to spawn on the node, and defaults to 1. The optional bind-to bind_addr[:port] specifies the IP address and port that

verify there are 4 threads at our disposal. julia> Threads.nthreads() 4 But we are currently on the master thread. To check, we use the function Threads.threadid julia> Threads.threadid() 1 Note If you it's fairly obvious that a given CPU will have fastest access to the RAM within the same computer (node). Perhaps more surprisingly, similar issues are relevant on a typical multicore laptop, due to differences defaults to current user, port to the standard ssh port. count is the number of workers to spawn on the node, and defaults to 1. The optional bind-to bind_addr[:port] specifies the IP address and port that