Hang after map_sync is called in loop for a number of iterations

The following script hangs after about ~180 iterations on my machine
Number of iterations it gets through seems to be dependent on the time elapsed (hence the sleep)
```
import numpy as np
import ipyparallel as ipp

c = ipp.Client()
dv = c[:]
dv.execute("import time")
dv.execute("import numpy as np")

v = c.load_balanced_view()

def fun(state):
time.sleep(0.5)
return np.random.normal()

# Generation loop
for it in range(1000):
inputs = range(12)
#v = c.load_balanced_view()
outputs = np.array(v.map_sync(fun, inputs))
print "Iteration", it
```
Windows 10, Anaconda installation
`ipyparallel 6.2.4 py27_0`

Cluster is started via `ipcluster start -n 4` on powershell
Tried and same problem observed with both python 2.7 and python 3.7
Tried both load balanced and direct views
No error messages and the powershell window for ipcluster becomes unresponsive

首先在 Windows 上使用 `ipcluster start -n 4` 執行 issue 的 Python 重現程式，並比較負載平衡和直接檢視兩種情況。追蹤 `map_sync` 在重複迭代後停止回應的位置；完成的標準是迴圈能在不掛起的情況下完成，且修正已針對回報的兩個 Python 版本完成驗證。

由索引模型根據 Issue 內容生成。