Pipelining in Redis

Redis Pipelining 

The Pipeline can help us fix this problem. Pipelines are not a novel technology or process; several have been employed in the past. In various network conditions, RTT will be varied. For example, the same computer room and computer room will be faster, whereas other computer rooms and areas will be slower. Redis has long supported Pipeline technology, so you can use it to manage Redis no matter what version you're using.

The pipeline may build a collection of Redis instructions, send them to Redis over RTT, and then execute the commands in the correct sequence and provide the results to the client. A pipeline was not used to execute N instructions in the preceding diagram; thus, the entire operation necessitates N RTTs. The following diagram illustrates how Pipeline may be used to execute N instructions with only one RTT:

Pipelining has been supported by Redis since its inception. Thus you may use it with any version of the database. Here's an example of how to use the raw Netcat utility:

$ (printf "PING\r\nPING\r\nPING\r\n"; sleep 1) | nc localhost 6379
+PONG
+PONG
+PONG

We don't pay the RTT fee for each call this time, but only once for the three orders.

To be clear, the order of actions in our first example with pipelining will be as follows:

• Client: INCR X
• Client: INCR X
• Client: INCR X
• Client: INCR X
• Server: 1
• Server: 2
• Server: 3
• Server: 4

Code

In the following benchmark, we'll utilize the Redis Ruby client, which supports pipelining, to see if pipelining improves performance:

require 'rubygems' //importing rubygems.
require 'redis'    //importing redis.
def bench(descr)
  start = Time.now
  yield
  puts "#{descr} #{Time.now - start} seconds"
end

def without_pipelining  //Iterating loop without the pipelining.
  r = Redis.new
  10_000.times do
    r.ping
  end
end

def with_pipelining     //Iterating loop the pipelining.
  r = Redis.new
  r.pipelined do
    10_000.times do
      r.ping
    end
  end
end

bench('without pipelining') do  //print time without the pipeline.
  without_pipelining
end
bench('with pipelining') do     //print time with the pipeline.
  with_pipelining
end

Output

without pipelining 1.185238 seconds
with pipelining 0.250783 seconds

Point to remember

When sending commands with Pipeline, the number of commands assembled by Pipeline at any given moment cannot be arbitrary. Otherwise, the amount of command data gathered at once will be excessive. On the one hand, it will lengthen the client's wait time. 
Operational database systems are aimed toward real-time, transactional processes, whereas traditional databases rely on batch processing.

Comparison

Consider the following distinctions between batch commands and Pipeline:

• The pipeline is non-atomic, whereas native batch instructions are atomic.
   
• Pipeline enables multiple batch commands, one command corresponding to several keys.
   
• The Redis server supports native batch commands, whereas Pipeline needs the server and client to be implemented together.

Frequently Asked Questions

1. In Redis pipelining, how many instructions may be transmitted to a server?
   In most circumstances, keeping the pipeline size between 100 and 1000 operations yields the greatest performance. However, you may conduct some benchmark studies using common queries that you submit.
    
2. What is Redis pipelining, and how does it work?
   Redis pipelining is a performance-enhancing approach that involves delivering numerous instructions at once without waiting for each one to respond.
    
3. How quickly is Redis created?
   Redis is 10 to 30% quicker when the data set fits into the working memory of a single computer.
    
4. Is there anything quicker than Redis?
   The database MongoDB is schemaless, which implies it doesn't have a set data structure. This means that when the size of the data in the database grows, MongoDB can run significantly quicker than Redis.
    
5. Is Redis a database or a cache?
   Although Redis was originally designed as a caching database, it has subsequently developed into the main database. Many modern apps utilize Redis as their primary database. Most Redis service providers, on the other hand, only support Redis as a cache, not as a primary database.

Conclusion

We studied how to optimize round-trip times by batching the Redis commands and strategy for increasing performance by giving numerous instructions at the same time without waiting for each one to respond. You can explore data types in Redis by clicking here.

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