dhis2-devs team mailing list archive

[Bob Jolliffe <bobjolliffe@xxxxxxxxx>]

hi

2010/10/22 Ola Hodne Titlestad <olati@xxxxxxxxxx>:
> 2010/10/22 Lars Helge Øverland <larshelge@xxxxxxxxx>
>>
>> Hi Bob
>> Sorry for not returning to this earlier, been battling with windows 64 bit
>> odbc drivers.
>>
>> 2010/10/22 Bob Jolliffe <bobjolliffe@xxxxxxxxx>
>>>
>>> Hi Lars, Ola and all
>>>
>>> Thinking about exporting pivot tables .. we need to pen up some
>>> requirements which we can get into a blueprint.  While we are
>>> considering that, I've given some thoughts below.
>>>
>>> My initial thought was that we would construct a pivot table with a
>>> jdbc connection like we would normally do manually, and then simply
>>> populate the pivot cache so that the spreadsheet would be
>>> "free-standing".  On reflection that is probably neither the best nor
>>> the simplest thing to do.  Playing around with excel (in wine :-)  I
>>> figured it is actually much more straightforward to have two sheets;
>>> one for the data and one for the pivot table.  The pivot table would
>>> operate on the data in the other worksheet.  This is more explicit
>>> than simply hiding the data in the pivot cache.  Though I need to test
>>> this a bit more.  If the pivotcache is an obligatory data store then
>>> it might not make sense to carry the data twice.  The pivot table
>>> constructs are fairly complex but not outlandishly so - once I'm done
>>> unpicking, I will write up a short description of the anatomy of a
>>> pivot table so we can see what needs to be done.
>>>
>>
>> This sounds just fine to me.
>
> This might work, just have in mind that we will then need several pairs of
> data+pivot worksheets as we want to have multiple pivot tables in an Excel
> file.
> Also have in mind that we can talk about up to around 1.500.000 rows (that's
> when my laptop starts to complain at least) of data here, so these data
> sheets will be large. Typically, number of rows of data will be somewhere
> around 200-600K.
>
>
>>
>>
>>>
>>> One possibility would be that the pivot table could be generated as
>>> part of the export of a report table ie. optionally export to excel or
>>> export to excel-with-pivot.
>>>
>>> Given that there is no advance indication of the columns in a report
>>> table, a challenge will be how and when to define the pivot model -
>>> ie. the pivot fields -  and how to persist that model (we don't want
>>> users to have to recreate the pivot model each time).  This will
>>> probably require an extra object in our data model (PivotModel) which
>>> defines the row and column pivot fields and data field, where a
>>> ReportTable can have a 0-* relationship with 0 or more PivotModels.  A
>>> possible beneficial side effect of this could be that we also leave
>>> open the ability to generate the pivot table rendition with things
>>> other than excel.  I don't see this as an immediate requirement but
>>> useful to have the pivotmodel abstraction anyway.  In reality the
>>> design of the pivotmodel will be based on what excel requires.
>>>
>>> Generating the excel spreadsheet off the reporttable+pivotmodel will
>>> produce an OOXML xlsx file - actually a bundle of xml streams which
>>> need to be zipped.  Its a bit unfortunate that M$ defines a flat file
>>> single xml for other OPC office documents, but sadly not excel.
>>> Dealing with a single flat file is much easier than zip containers
>>> with multiple streams but so be it.  At least they end up smaller.
>>> Though given that these reporttables can be very large I don't think
>>> an xslt approach is really the most efficient at least for producing
>>> the data worksheet.  It might make sense if the source data was xml,
>>> but even then probably not.  So simple iteration through the table
>>> rows with a stax writer will work best.  The second sheet (the pivot
>>> sheet) would just be a serialization of the pivot model.
>>>
>>> We will probably have to implement the excel optimization of
>>> sharedstrings (where literal strings are not written into the
>>> spreadsheet - just index values from a table).  This adds complexity
>>> but I think we are talking pretty large files here.  If we don't do
>>> the sharedstrings optimization, Excel will do it anyway the first time
>>> it opens and saves the file, but I suspect we will have to do it up
>>> front.
>>>
>>> Regarding UI and PivotModel I want to take a look at our existing work
>>> on web pivot tables to see whether we can't leverage some of this.  If
>>> we follow roughly the outline above the user would have the option to
>>> define 0 or more pivottable definitions at the time of creating, or
>>> editing, a reporttable.  What do you think?  Is the above close to
>>> what you guys have in mind.  Lets hammer out some requirements and
>>> create the blueprint.
>>>
>>
>> We won't base this on report tables as (at least I) can't see any huge
>> benefits. The excel pivot tables themselves are more capable of having
>> dimensions on columns, rows, filters than our report tables. In fact we
>> usually use a SQL view as datasource for the pivot tables - which has a
>> fixed number of columns. The view is based on the aggregateddatavalue table
>> and joins in the dataelement, orgunit, period and periodtype tables. In
>> addition we join in a series of resource tables to get information about the
>> orgunit structure, dataelement groupset structure, orgunit groupset
>> structure (additional dimensional information!) to make the pivot table more
>> valuable for analysis. (This also goes for indicators.)
>> Since this should be more of a offline analysis tool I think exporting all
>> dataelements/indicators will be most appropriate. The user interface could
>> simply request a start and endate (and/or relative periods), indicators vs
>> dataelements, parent organisation unit and organisation unit level. Ola will
>> maybe have some views here...
>
> Agree with Lars, I don't think report tables should be used as source for
> pivot tables, at least not for the standard "ALL data" pivot tables.

Yes I understand that now

> For
> more ad-hoc use the pivots generated off a report table might be useful as
> an export option, but let's start with the most common use cases, the big
> pivot tables with all the data for browsing and data analysis.
> The pivot source views (sql) that we have used e.g. in the newly distributed
> pivots for the demo database can be found in an email to the list on Sep 21,
> together with the pivots and the database dumps:
> http://www.mail-archive.com/dhis2-devs@xxxxxxxxxxxxxxxxxxx/msg07341.html ;(from
> Sep 21)
> These views have been stable for a long time and describe the fields of the
> basic pivot tables that are needed for DHIS data analysis.
> These set of fields go back as far as DHIS 1.3, so the basic pivot tables
> are stable and we know their structure, basically the core data dimensions
> of DHIS2 (see chapter 2 in user manual).
> What always will be variables are the orgunit level of aggregation for the
> data or indicator values and the period type. You will see these two are
> specified at the end of every where clause in the pivot views. These are
> used as a filters when fetching data from the data mart.
> If you open the pivot table for download in that email you can follow my
> reasoning below:
> Typically we have two tables for monthly (raw data+indicator data) for the
> lowest level plus at least two more for a higher level. E.g. in the demo
> based on SL we use the health facility level (level 4) and the Chiefdom
> level (3). The reason for using Chiefdom level as well is that these tables
> are much faster to manipulate since there are a lot less data when shaving
> away the lowest level. How many levels and which levels to put in the pivot
> table will vary from place to place. In addition to these at least four
> tables,  there is often at least one table for population data, which has a
> yearly period type and therefore needs a separate view and table. So for the
> demo database we have 5 basic tables which covers all the data for data
> elements and indicators. This set of pivot tables is what I would define as
> a minimum pivot table setup for a DHIS database. Over time (depending on the
> amount of data collected) it might be necessary to split up these basic
> tables by year since they can get too big for excel to handle. Such a split
> can be facilitated by a simple from and to filter on the start date in the
> period field in the sql.
> Then there can be many more customised pivot tables which make use of
> additional dimensions to the data like the data element categories, and data
> element and orgunit group sets. The simplest approach there is to (still
> talking sql) do a select * from the various resource tables. Then you will
> have a data source for all other customised tables (using the same period
> type and aggregation level). Working with data element categories in pivot
> tables it doesn't make sense to use too many at the same time, and rather
> work on data elements that share the same categories (within or across
> datasets). You can see in the demo pivot table file that we have set up
> multiple tables making use of data element categories (EPI, RCH, HIV etc.).
> These are all using the same source data (chiefdom level monthly raw data),
> but are using different pivot fields (columns in the result set). The total
> number of available fields are the same for all these custom chiefdom
> tables, but we are only using a small subset of these fields in each table.
> This means that the same data source could also be used for the basic tables
> (the two chiefdom tables at least), and just select even fewer fields in the
> table. The users can also easily add more fields to a table in Excel, using
> drag and drop functionality.
> It seems to me that there is a need to separate between the source data and
> the pivot structure, to reuse the source data in multiple tables. I think
> that is how Excel is thinking too, but it doesn't always seem to work that
> way, e.g. when creating a copy of an existing worksheet with a pivot  table.

Yes we can ask excel pivot tables to use common pivot table cache.

> I am not sure how much of this customisation we need to support inside DHIS2
> and how much we can leave to Excel (which has nice tools for copying tables,
> drag and drop pivot fields etc.). First we need to come up with something
> that works for the basic tables and then look at these more custom use
> cases.
> When it comes to pivot tables using period types other than monthly or
> yearly (both covered in the basic tables listed above), like six-monthly,
> quarterly or weekly these are also important to support. The pivot fields
> are the same as in the basic tables, it is just a different periodtype
> filter on the data source, so these might be easier to accommodate.
> Looking at the next steps, to me the key new features that I would like to
> see with regards to pivot tables are:
> 1) a pivot table update service, where users that are on the online server
> (no local install) can update their local pivot tables against the online
> DHIS server
> Since a pivot table can contain months and years of data we do not want to
> download the full tables every month, but simply append the latest month of
> data to the existing local pivot tables
> 2) a pivot generator, where the users can download a new pivot table file
> directly off a DHIS2 server without having to do any local configuration
> etc. , and then later use the update service to update their tables
> with 1) being the most critical and urgent, but I realise that we might need
> 2) first, in order to deal with a standard set of tables and pivot data

Yes I think 1 can only really work in concert with 2.  Since we can't
ask dhis to update any old pivot table, it will need to be a
pivottable which it is intimately familiar with - which is either a
fixed format one as you have discussed or one that is created through
dhis.  Naturally we start with former.   BTW looking at size of tables
I have dropped the idea of holding data in a worksheet.  This does in
fact produce duplication of data which is also held in cache and both
unfortunately also held in memory.  So we work only with the hidden
pivot table cache as the local store.

Thinking how and where data is being moved, it might not make sense to
pass the (massive) excel file back and forwards to dhis in order to
get updates injected.  That might defeat the purpose. Which raises
some questions.  Either we have a standalone tool which grabs
incremental update from dhis and appends to excel pivottable cache or
we have some sort of VBA macro defined within excel. I think the
latter might prove problematic - like performing circumcision on
oneself whilst awake, it might cause excel to breakdown.  So probably
a standalone tool ..

I haven't worked through the samples yet.  I think I will buy excel on
the weekend and invoice Jorn.

Cheers
Bob

> sources in 1).
> Ola
> ---------
>
>>
>> When it comes to SQL views we have recently implemented a function for
>> this where SQL views can be persisted as an application object and
>> re-generated at any time. This means we can compile in a few default SQL
>> views which can be used for this in DHIS. As you say an iteration over the
>> rows in this view with eg. a stax writer would work.
>> Ola/I have made some samples.
>> Demo database with SQL
>> views: http://folk.uio.no/larshelg/files/dhis2sl.backup
>> Small pivot table based on the aggregateddatavalue orgunit level 2
>> view: http://folk.uio.no/larshelg/files/dataou2.xlsx
>> Bigger pivot table based on the aggregateddatavalue orgunit level 3
>> view: http://folk.uio.no/larshelg/files/dataou3.xlsx
>> If you want to create more pivot tables install postgres on windows
>> here: http://www.postgresql.org/download/
>> Then install psql odbc windows
>> here: http://www.postgresql.org/ftp/odbc/versions/msi/
>> You can create a data source directly from Excel by going to Data - From
>> other sources - From Microsoft Query and choosing the postgres odbc driver
>> under 2. (Stay clear of x64! :)
>> Your thoughts on shared string optimizations and zipped stream bundles
>> sound fine to me, in any case you know better here:)
>> regards, Lars
>>
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>
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