For that approach I would think either the MapCache or the File would work. The trick will be getting the max value out of the flow file. After QueryDatabaseTable you could split the Avro and convert to JSON (or vice versa), then update the MapCache or File. I'm not sure the order of records is guaranteed, I recall an issue with the FIFO prioritizer when all the files have the same created date (which was fixed in 1.0, not sure about 0.7.x). An alternative is to use a scripting processor to guarantee that you only overwrite the value if it is greater than what's in the cache/file. I've got an an example in Groovy for reading the MapCache: http://funnifi.blogspot.com/2016/04/inspecting-your-nifi.html
I'm not near my computer at the moment, does PutDistributedMapCache have an option to store only if greater than the existing value? If not, that might be a helpful improvement. Regards, Matt > On Aug 3, 2016, at 10:02 AM, Conrad Crampton <conrad.cramp...@secdata.com> > wrote: > > Hi, > Thanks for this. > I did think about a MV but unfortunately I haven’t access to create views – > just read access. That would have been my simplest option ;-) Life’s never > that easy though is it? > The only part of the sql I need to be dynamic is the date parameter (I could > even use the id column). Instead of using the MapCache (if that isn’t a good > idea), could I use the GetFile to just pull a single txt file with the > parameter (i.e. last run or max id value from the last run), which creates > flowfile, read that value and pass that into ExecuteSql (using the > aforementioned value as the parameter in the sql) as the select query can be > dynamically constructed from attributes/ flowfile content (as per docs)? And > then finally write text file back to file system to be picked up next time? > Thanks > Conrad > > On 03/08/2016, 14:02, "Matt Burgess" <mattyb...@gmail.com> wrote: > > Conrad, > > Is it possible to add a view (materialized or not) to the RDBMS? That > view could take care of the denormalization and then > QueryDatabaseTable could point at the view. The DB would take care of > the push-down filters, which functionally is like if you had a > QueryDatabaseTable for each table then did the joins. > > In NiFi 1.0 there is a GenerateTableFetch processor which is like > QueryDatabaseTable except it generates SQL instead of executing SQL. > That might be used in your a) option above but you'd have to reconcile > the SQL statements into a JOIN. A possible improvement to either/both > processors would be to add attributes for the maximum value columns > whose values are the maximum observed values. Then you wouldn't have > to parse or manipulate the SQL if you really just want the max values. > > I have been thinking about how QueryDatabaseTable and > GenerateTableFetch would work if they accepted incoming flow files (to > allow dynamic table names for example). It's a bit more tricky because > those processors run without input to get max values, so their > behavior would change when a flow file is present but would return to > the original behavior if no flow file is present. Since the > ListDatabaseTables processor is also in 1.0, it would be nice to use > that as input to the other two processors. > > I'm definitely interested in any thoughts or discussion around these > things :) > > Regards, > Matt > > On Wed, Aug 3, 2016 at 8:37 AM, Conrad Crampton > <conrad.cramp...@secdata.com> wrote: >> Hi, >> >> My use case is that I want to ship a load of rows from an RDMS periodically >> and put in HDFS as Avro. >> >> QueryTable processor has functionality that would be great i.e. maxcolumn >> value (there are couple of columns I could use for this from the data) and >> it is this functionality I am looking for, BUT the data is not from one >> single table. The nature of the RDBMS is that the business view on the data >> requires a bunch of joins from other tables/schemas to get the correct Avro >> file so the options I appear to have are >> >> a) Use QueryTable for each table that make up the business view and do >> the joins etc. in HDFS (Spark or something) – or potentially do the >> reconciliation within NiFi??? >> >> b) Use ExecuteSQL to run the complete SQL to get the rows which can >> easily be put into HDFS as Avro given that the line will be the business >> (denormalised) data that is required. >> >> The problem with a) is the reconciliation (denormalisation) of the data and >> the problem with b) is how to maintain the maxcolumn value so I only get the >> data since the last run. >> >> >> >> In order to address b) can I use the DistrubutedMapCacheServer & Client to >> hold a key/value pair of last run date and extract from this date as a >> parameter? >> >> >> >> Thanks for any suggestions. >> >> >> >> Conrad >> >> >> >> SecureData, combating cyber threats >> >> ________________________________ >> >> The information contained in this message or any of its attachments may be >> privileged and confidential and intended for the exclusive use of the >> intended recipient. 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