在pyRserve中使用芹菜进行r-并行编程

Question

我有一个由时间序列组成的数据帧。

日期索引|时间序列1|时间序列2|。。。等等

我使用pyRserve运行了一个使用R.的预测函数

我想使用芹菜来实现并行处理。我已经在以下上下文中编写了工作者代码。

def pipeR(k #input variable):
    conn = pyRserve.connect(host = 'localhost', port = 6311)
    # OPENING THE CONNECTION TO R
    conn.r.i = k
    # ASSIGNING THE PYTHON VARIABLE TO THAT OF IN THE R ENVIRONMENT
    conn.voideval('''
    WKR_Func <- forecst(a)
    {
    ...# FORECASTS THE TIMESERIES IN COLUMN a OF THE DATAFRAME
    }
    ''')
    conn.eval('forecst(i)')
    # CALLING THE FUNCTION IN R
group(pipeR.s(k) for k in [...list of column headers...])()

为了实现并行处理，我可以为所有工作进程都有一个单独的端口吗（就像我在上面的代码中所做的那样，端口：6311），或者我应该为不同的工作进程有不同的端口吗？？

我当前收到一个错误

socketConnection中的错误（"localhost"，port=port，server=TRUE，blocking=TRUE，：无法打开连接

在R.中

Answer 1

当我为每个工作进程打开不同的端口时，问题得到了解决。。。

def pipeR( k, Frequency, Horizon, Split, wd_path):
    # GENERATING A RANDOM PORT
    port = randint(1000,9999)
    # OPENING THE PORT IN THE R ENVIRONMENT
    conn0 = pyRserve.connect(host = 'localhost', port = 6311)
    conn0.r.port = port
    conn0.voidEval
    ('''
        library(Rserve)
        Rserve(port = port, args = '--no-save')
     ''')
    # OPENING THE PORT IN THE PYTHON ENVIRONMENT
    conn = pyRserve.connect(host = 'localhost', port = port)
    # ASSIGNING THE PYTHON VARIABLE TO THAT OF IN THE R ENVIRONMENT
    conn.r.i = k
    conn.voideval
    ('''
     WKR_Func <- forecst(a)
     {
     ...# FORECASTS THE TIMESERIES IN COLUMN a OF THE DATAFRAME
     }
     ''')
    conn.eval/('forecst(i)')
    conn0.close()