Hi,
I am getting wrong results with OpenDAP requests on ncml aggregation when
using strides. THREDDS sometimes give an error message and sometimes the output
is plain wrong. It seems to be working fine with regular netCDF files.
To demonstrate this I have created two files the first file is a regular netcdf file
with one variable (with name "time") and one dimension of size 14:
http://data.nodc.noaa.gov/thredds/catalog/testdata/strides/catalog.html?dataset=testdata/strides/agg.nc
The values for the variable range from 1 to 14.
The second is an ncml aggregation which is equivalent to the first file,
aggregated along the single dimension. The ncml aggregation has four files-
first file with dimension 5, second with 3, third with 2 and fourth with 4
(adds up to 14):
http://data.nodc.noaa.gov/thredds/catalog/testdata/strides/catalog.html?dataset=testdata/strides/agg_thredds.ncml
Now, when I issue OpenDAP requests with strides, I get the following output
Request Output from the regular NetCDF
Output from the NCML aggregation(- - - - - | - - - | - - | -
- - -)
------------
---------------------------------------------
-------------------------------------------------
time[0:1:13] 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 (correct)
time[0:2:13] 1, 3, 5, 7, 9, 11, 13
1, 3, 5, 7, 9, 11, 13
(correct)
time[0:3:13] 1, 4, 7, 10, 13
1, 4, 8, 12, 0
(incorrect)
time[0:4:13] 1, 5, 9, 13
message = "NcSDArray
java.lang.ArrayIndexOutOfBoundsException=null for request= NcSDArray read time
time(0,4,13) ...
time[0:5:13] 1, 6, 11
1, 6, 11
(correct)
time[0:6:13] 1, 7, 13
1, 0, 0
(incorrect)
time[0:7:13] 1, 8
1, 0
(incorrect)
time[0:8:13] 1, 9
1, 9
(correct)
time[0:9:13] 1, 10
1, 0
(incorrect)
time[0:10:13] 1, 11
1, 11
(correct)
time[0:11:13] 1, 12
1, 0
(incorrect)
time[0:12:13] 1, 13
1, 0
(incorrect)
time[0:13:13] 1, 14
1, 0
(incorrect)
time[0:14:13] 1
1
(correct)
There seems to be some pattern to whenever it gives incorrect results. After
jumping from one dataset to a subsequent one in the aggregation, if the new
index doesn't correspond to the first value in the subsequent dataset, it gives
incorrect results.
Upendra
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