我还没有找到太多的教程使用自定义函数包。
假设我有以下数据集：

UID : distance_from_something : timestamp
100:100:0
100:101:1
100:102:2
200:200:0
200:202:3
200:204:6
300:300:0
300:303:5

现在我要计算每个液体的速度

data = LOAD 'testfile' USING PigStorage(':') AS (
    uid:long,
    distance:int,
    time_raw:long);

SPLIT data INTO
    good_data IF (
        (uid > 0L)),
    bad_data OTHERWISE;

REGISTER '$UDFPATH//calculateVelocity.py' USING jython AS vcalc;

grouped_data = GROUP good_data BY (long)$0;
data = FOREACH grouped_data GENERATE vcalc.calculate(good_data);
flat_data = FOREACH data GENERATE FLATTEN($0);

这是做这类事情的好方法吗？例如，如果我希望输出看起来像：

100:100:0:1
100:101:1:1
100:102:2:1
200:200:0:0.666...
200:202:3:0.666...
200:204:6:0.666...
300:300:0:0.6
300:303:5:0.6

在这种情况下，用非线性插值计算速度的最佳方法是什么？
这是我当前的占位符：

def compared_to_previous(bag, index):
    dx = float(bag[index][1] - bag[index - 1][1])
    dt = float(bag[index][-1] - bag[index - 1][-1])/1000
    return dx/dt

def compared_to_next(bag, index):
    return compared_to_previous(bag, index+1)

def calculate(inBag):
    outBag = []

    index = 0
    tuples = len(inBag)
    for t in inBag:
        row = list(t)
        if not index:
            row.append(compared_to_next(inBag, index))
        elif index == tuples - 1:
            row.append(compared_to_previous(inBag, index))
        else:
            v = compared_to_previous(inBag, index)
            v += compared_to_next(inBag, index)
            row.append(v/2)
        outBag.append(tuple(row))

    return outBag