Thanks John. I am glad it was useful.
Upendra
On 7/2/2011 1:56 PM, John Caron wrote:
Hi Upendra:
Yes you are right. There a bug in reading strided subsets of
joinExisting aggregations. Ill have a fix out early next week. Thanks
for seeing that and your very fine test to reproduce it!
John
On 7/1/2011 9:27 AM, Upendra.Dadi@xxxxxxxx wrote:
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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