利用Scala轻松连接Redis(scala连接redis)
Recent years, with the rapid development of technology , data-driven has become the mnstream of the development ideas all over the world. As a lightweight and efficient non-relational database, Redis has become one of the most widely used databases in the current market, which is welcomed by developers due to its easy-to-use, high performance, rich functions and low cost of mntenance. If Redis is combined with a strong language such as Scala to write programs, developers can easily and fast to complete the task of data-modeling and data analysis.
In this paper, I am honored to introduce the techniques of connecting Redis with Scala.
The mn goal here is to connect Scala application with Redis Database and use the functionality of Redis to manipulate the data inside the application. Before going ahead, it is assumed that you have installed and configured Redis in your local machine.
First of all, we need to initialize the Jedis network library for which we can configure redis host and port.
// Redis server host and port
val redisHost = “localhost”
val redisPort = 6379
// Create a JedisConnectionPool
val pool = new JedisConnectionPool(new JedisPoolConfig(), redisHost, redisPort)
Secondly, we need to decide which Redis client protocol to use. Here I am going to use Redis stand-alone protocol.
Lastly, let’s see how we can use Jedis library to create a connection instance and use that to execute commands like Set, Get, expire, delete and so on.
// Create a pooled connection
val connection = pool.getResource
// Set a Key – value pr
connection.set(“key”, “value”)
// Get the value of Key
val value = connection.get(“key”)
// Close the connection
connection.close()
The above code snippet does not represent the entire functions of Redis. We can also use Jedis connection to manipulate list, sets and other data structures using various API provided by the library.
All in all, by combining Scala and Redis, developers can not only manipulate the data of Redis databases, but also complete data-modeling and data analysis tasks easily and fast. By mitigating the burden of database administration, we are enabled to focus more on the business logic development.