# Where is error message on the remote worker?

**URL:** https://discourse.julialang.org/t/where-is-error-message-on-the-remote-worker/28898
**Category:** General Usage
**Tags:** question, parallel
**Created:** [September 18, 2019, 3:42pm UTC](https://discourse.julialang.org/t/where-is-error-message-on-the-remote-worker/28898 "2019-09-18T15:42:22Z")
**Posts on this page:** 1
**Showing post:** 3

<div class="post-metadata">

### Author: ![Chong\_Wang](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chong_wang/32/20307_2.png) [@Chong\_Wang](https://discourse.julialang.org/u/Chong_Wang)
#### Post date: [September 19, 2019, 10:58pm UTC](https://discourse.julialang.org/t/where-is-error-message-on-the-remote-worker/28898/3 "2019-09-19T22:58:40Z")

</div>

I understand that `remotecall_fetch` will return the error. However, the function that is going to be executed on the remote process will never return and will always be waiting for tasks from the master process:

```julia
mutable struct ParallelFunction
    jobs::RemoteChannel
    results::RemoteChannel
    nreceived::Int64
    ntaken::Int64
end

function do_work(f, jobs, results, args...)
    while true
        x = take!(jobs)
        result = f(x, args...)
        put!(results, (x, result))
    end
end

function ParallelFunction(f, args...; len=128)
    jobs = RemoteChannel(()->Channel{Any}(len))
    results = RemoteChannel(()->Channel{Any}(len))
    for p in workers()
        remote_do(do_work, p, f, jobs, results, args...)
    end
    return ParallelFunction(jobs, results, 0, 0)
end

function give!(pf::ParallelFunction, x)
    put!(pf.jobs, x)
    pf.nreceived += 1
end

function get!(pf::ParallelFunction)
    result = take!(pf.results)
    if result[2] isa ErrorException
        throw(result[2])
    end
    pf.ntaken += 1
    return result
end

```

Suppose a function `f` has four arguments `x`, `a`, `b` and `c`. The purpose is to evaluate the function `f` at several different `x`s with fixed argument `a`, `b` and `c`.  
A `ParallelFunction` can be constructed as

```julia
pf = ParallelFunction(f, a, b, c; len=128)

```

To evaluate the function `f` at `x1`, `x2` and `x3`, the following statement can be used

```julia
give!(pf, x1)
give!(pf, x2)
give!(pf, x3)

```

The function will be evaluated in parallel on any possible processes. To obtain the result:

```julia
for i in 1:3
    println(get!(pf))
end

```

`get!(pf)` returns a tuple, the first element of the tuple is the argument `x` and the second argument is the corresponding result.

However, it is possible that the user forget to define the function `f` on the remote process. In this case, the `get!(pf)` will hang indefinitely, which is not a desirable result. I want to throw an error if this is the case.

---

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