>> From: Roland Viger <rviger@xxxxxxxx>
>> Date: January 26, 2010 1:19:02 PM CST
>> To: Lauren E Hay <lhay@xxxxxxxx>
>> Cc: John Caron <caron@xxxxxxxxxxxxxxxx>, Steven Markstrom
>> <markstro@xxxxxxxx>, netcdf-java <netcdf-java@xxxxxxxxxxxxxxxx>, Nate Booth
>> <nlbooth@xxxxxxxx>, Rich Signell <rsignell@xxxxxxxx>
>> Subject: Re: [netcdf-java] point data
>>
>>
>> Hi John,
>>
>> I'll try to add a bit to Lauren's response. Hopefully the others will make
>> sure I'm not mangling the technology or vision on this. So, yes on all
>> three types of queries (including Lauren's additional one), but it might be
>> the case that Lauren's case #3 (with a time period) is the only one that
>> needs to be supported if we use a metadatabase to answer the rest of the
>> questions (location, period of record, data quality, etc) before querying
>> the actual data store. We might need to think about this on our end a
>> little more.
>>
>> As far as web services, we're expecting to serve all this through THREDDS
>> or direct NetCDF reads. As far as clients, our first focus will be stuff we
>> make ourselves. Home made web page interfaces and Java applications are the
>> most important for the short term. Access to the data from other data
>> servers (other instances of THREDDS, RAMADDA, or non-Unidata products like
>> ERDDAP) is also on the horizon, but not really in the initial development
>> cycle (Nate, Steve, do you agree with this?). These other data servers may
>> or may not be local to the data. We're open to suggestions--as Lauren said,
>> we're just expecting to use OPeNDAP and/or direct reads with Java-NetCDF.
>> If there are libraries or classes that we should be lifting out of IDV or
>> otherwise leveraging, we would be very interested to hear about this. We
>> have not really investigated the Unidata display and analysis offerings at
>> all.
>>
>> I think the integer w/float offset plan sounds good as long as we can
>> return the data in the original floating point form. Doesn't seem like
>> carrying that transformation out is a big deal. Could it be embedded in the
>> creation/streaming of the original NetCDF file that gets returned? Would be
>> nice to avoid writing one NetCDF file, reading it, and then writing
>> out/streaming the real result.
>>
>> Separating current and archived data might be a help, although our data set
>> is updated only every couple of months. The "current" thing is not all that
>> dynamic for us. Using this idea to break the history into conveniently
>> sized blocks optimized for access should probably be our focus. Chunking
>> might be good since some of our data sets go back a lot of years. I take it
>> that NcML would be used to stich the chunks together as a single,
>> temporally continuous virtual file.
>>
>> Part of our question about the arrangements of files is that we've normally
>> had the full history each station in a separate file. We weren't sure yet
>> how to use NcML to stitch these together. Rich says you've figured out how
>> to do this spatial kind of stitching. We didn't know if this was the most
>> efficient or whether to simply regenerate the NetCDF files according to
>> other dimensions/variables. Not sure if we're closer to answering your
>> question on this. Please let us know.
>>
>> Roland
>> |----------+--------------------------------------------------------------|
>> |From: |Lauren E Hay/WRD/USGS/DOI |
>> |----------+--------------------------------------------------------------|
>> |To: |John Caron <caron@xxxxxxxxxxxxxxxx> |
>> |----------+--------------------------------------------------------------|
>> |Cc: |Steven Markstrom <markstro@xxxxxxxx>, netcdf-java |
>> | |<netcdf-java@xxxxxxxxxxxxxxxx>, Nate Booth <nlbooth@xxxxxxxx>,|
>> | |Rich Signell <rsignell@xxxxxxxx>, Roland Viger |
>> | |<rviger@xxxxxxxx> |
>> |----------+--------------------------------------------------------------|
>> |Date: |01/25/2010 02:35 PM |
>> |----------+--------------------------------------------------------------|
>> |Subject: |Re: [netcdf-java] point data |
>> |----------+--------------------------------------------------------------|
>>
>>
>>
>>
>>
>>
>>
>>
>>
>> John
>> Below are the answers to your questions -- let me know if it's not enough
>> info.
>> Lauren
>> ======================================
>> Lauren E. Hay, Ph.D. Tel: (303) 236-7279
>> U.S. Geological Survey Fax: (303) 236-5034
>> Box 25046, MS 412, DFC Email: lhay@xxxxxxxx
>> Lakewood, CO 80225
>> ======================================
>>
>>
>> |---+---------------------------------------------------------------------|
>> |Fro|John Caron <caron@xxxxxxxxxxxxxxxx> |
>> |m: | |
>> | | |
>> |---+---------------------------------------------------------------------|
>> |To:|Rich Signell <rsignell@xxxxxxxx> |
>> | | |
>> |---+---------------------------------------------------------------------|
>> |Cc:|netcdf-java <netcdf-java@xxxxxxxxxxxxxxxx>, Roland Viger |
>> | |<rviger@xxxxxxxx>, Steven Markstrom <markstro@xxxxxxxx>, Lauren E Hay|
>> | |<lhay@xxxxxxxx>, Nate Booth <nlbooth@xxxxxxxx> |
>> |---+---------------------------------------------------------------------|
>> |Dat|01/25/2010 10:21 AM |
>> |e: | |
>> | | |
>> |---+---------------------------------------------------------------------|
>> |Sub|Re: [netcdf-java] point data |
>> |jec| |
>> |t: | |
>> | | |
>> |---+---------------------------------------------------------------------|
>>
>>
>>
>>
>>
>>
>>
>>
>> Hi Rich and all:
>>
>> This is a interesting challenge on such a large datasets to get good read
>> response.
>>
>> First, you have to decide what kinds of queries you want to support and
>> what kind of response time is needed. I have generally used the assumption
>> that the common queries that you want to optimize are:
>> 1) get data over a time range for all stations in a lat/lon box.
>> 2) get data for a single station over a time range, or for all time.
>> 3) get data with a specified list of stations
>>
>>
>> Usually I would break the data into multiple files based on time range,
>> aiming for a file size of 50-500 Mb. I also use a different format for
>> current vs archived data, so that the current dataset can be added to
>> dynamically, while the archived data is rewritten (once) for speed of
>> retrieval.
>>
>> Again, all depends on what queries you want to optimize so ill wait for
>> your thoughts on that.
>> We ran into this problem in the past so we made a separate file for each
>> station and each variable. Is there a problem with having too many files?
>> Can we have a file by year that only contains stations with data for that
>> year? Or -- if we don't care how many files -- 1 file for each station for
>> each variable for each year. It does not matter to me. The current project
>> will have data that has a set time period. We hope to use this structure
>> for other projects that will have file updates as new data is collected.
>>
>> Another question is what clients need to access this data. Are you writing
>> your own web service, do you just want remote access from IDV, or ??
>> We anticipate that our web serivces will use the OpenDAP API. I'm not the
>> person to answer this one.
>>
>>
>> I would think that if we're careful, we can get netcdf-4 sizes that are
>> similar to compressed text, but we'll have to experiment. The data appears
>> to be integer or float with a fixed dynamic range, which is amenable to
>> storing as an integer with scale/offset. integer data compresses much
>> better than floating point due to the noise in the low bits of the
>> mantissa. So one task you should get started on is to examine each field
>> and decide its data type. if floating point, decide on its range and the
>> number of significant bits.
>>
>>
Hi John,
With regard to the station data with daily observations, here is current
use-case/work-flow we are looking at.
1) Subset stations by lat/long bounding box (and possibly date range)
2) For each station in subset output station observation per date for desired
date range (this is a pivot against the organization of station data in the
CDM).
What we are struggling with is how to store, serve and read this data in a
client/server environment. My fear from looking at the Station Observation CDM
and the NetCDF Java API is that we will end up forcing non-sequential reads at
the THREDDS server (as we loop through the data steps and read data for each
station). Couple this with the client side read buffering (if it's optimized
for sequential access) in the NetCDF java library and I'm afraid that well be
pulling much more data across the wire than we need.
In addition to determining how we should store the data we need to figure out
how to read it...
Thanks,
Tom
