IndexError when trying to Fill Gaps in Time Series using pd.DataFrame.resample
#### Code Sample
```
df = pd.read_hdf(file_path, key="alarms")
df['acqTime'] = pd.to_datetime(df['acqTime'], unit='s')
df.set_index('acqTime', inplace= True)
df.sort_index(inplace=True)
df = df.resample("2S").fillna("backfill")
```
#### Problem description
I am trying to fill gaps in my time-series by resampling data every 2 seconds. Sometimes it may be the case the number of missing data points are even or odd. I want to even it out for 2 seconds. 

But using the code above I get the following error:
```

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
BigQuery.py", line 94, in <module>
    data = p.map(worker_partial, alarms[:2])
lib\multiprocessing\pool.py", line 268, in map
    return self._map_async(func, iterable, mapstar, chunksize).get()
  File lib\multiprocessing\pool.py", line 657, in get
    raise self._value
ValueError: cannot reindex a non-unique index with a method or limit
```

####  Output Description

## Before Resampling: 
```
[Timestamp('2018-10-16 05:13:38'),
 Timestamp('2018-10-16 05:13:40'),
 Timestamp('2018-10-16 05:13:42'),
 Timestamp('2018-10-16 05:13:44'),
 Timestamp('2018-10-16 05:13:47'),
 Timestamp('2018-10-16 05:13:55),
]
```
After Resampling Expected Output: 
```
[Timestamp('2018-10-16 05:13:38'),
 Timestamp('2018-10-16 05:13:40'),
 Timestamp('2018-10-16 05:13:42'),
 Timestamp('2018-10-16 05:13:44'),
 Timestamp('2018-10-16 05:13:46'),
 Timestamp('2018-10-16 05:13:47'),
 Timestamp('2018-10-16 05:13:49'),
 Timestamp('2018-10-16 05:13:51'),
 Timestamp('2018-10-16 05:13:53'),
 Timestamp('2018-10-16 05:13:55'),
]
```

#### Output of ``pd.show_versions()``
```
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.24.2
pytest: None
pip: 19.1.1
setuptools: 41.0.1
Cython: None
numpy: 1.16.4
scipy: 1.3.0
pyarrow: None
xarray: None
IPython: 7.5.0
sphinx: None
patsy: None
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: None
tables: 3.5.2
numexpr: 2.6.9
feather: None
matplotlib: 3.1.0
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: 0.10.0
pandas_datareader: None
gcsfs: None
​
```
<details>

[paste the output of ``pd.show_versions()`` here below this line]

</details>
