2022-04-03 00:48:29 -04:00
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* setup postgres db with a username and password and database
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* add this to .bashrc to quickly invoke command line connection `export PGD="psql -U ptrowbridge -d ubm -p 5433 -h 192.168.1.110"`
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2020-10-23 00:19:39 -04:00
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setup
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----------------------------------------------------------------------------------------------------------------------------------------------------
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2022-04-03 00:48:29 -04:00
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* setup the application tables `$PGD -f setup_sql/schema.sql`
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* create a table of data to forecast
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* edit `target_info.sql` to reflect the name of the table from previous step
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* `$PGD -f setup_sql/target_info.sql` to populate the meta table
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* fill out the `target_meta` table in the database to model the forecast table
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* `PGD -f setup_sql/build_maste_tables.sql` to create master data tables from forecast data
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* `./routes/baseline/generate_route_sql.sh` to create the baseline sql used by the /baseline route
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2020-10-23 00:19:39 -04:00
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2022-04-12 22:58:31 -04:00
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| schema | tname | cname | opos | func | fkey | fcol | dtype | appcol | pretty |
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| ------- | ------- | -------------- | ---- | ------------ | ------------ | -------------- | ------- | ------------ | ------ |
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| fc | live | fb_cst_loc | 91 | cost | | fb_cst_loc | numeric | | |
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| fc | live | ship_cust | 36 | scust | scust | ship_cust | text | | |
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| fc | live | rdate | 98 | rdate | rdate | drange | date | | |
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| fc | live | geo | 42 | scust | | geo | text | customer | |
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| fc | live | part | 54 | item | item | part | text | item | |
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| fc | live | odate | 96 | odate | odate | drange | date | order_date | |
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| fc | live | sdate | 100 | sdate | sdate | sdate | date | ship_date | |
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| fc | live | oseas | 97 | odate | | ssyr | integer | | |
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| fc | live | calc_status | 94 | order_status | order_status | calc_status | text | order_status | |
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| fc | live | rseas | 99 | rdate | | ssyr | integer | | |
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| fc | live | sseas | 101 | sdate | | ssyr | integer | | |
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| | | | | | | | | version | |
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| | | | | | | | | iter | |
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| | | | | | | | | logid | |
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* func: table name of associated data
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* fkey: primary key of assoicated dat
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* fcol: associated field from the master data table if it is different (oseas would refer to ssyr in fc.perd)
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* pretty: display column name (user friendly)
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* appcol: parameters that will have to be supplied but the application
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* order_date
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* ship_date
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* customer
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* item
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* order_stats
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* units
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* cost
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* value
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* version (added if missing)
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* iter (added if missing)
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* logid (added if missing)
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2020-10-30 00:56:48 -04:00
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routes
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2020-10-23 00:19:39 -04:00
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----------------------------------------------------------------------------------------------------------------------------------------------------
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2020-10-30 00:56:48 -04:00
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* all routes would be tied to an underlying sql that builds the incremental rows
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* that piece of sql will have to be build based on the particular sales layout
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* **columns:** a function to build the columns for each route
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* **where** a function to build the where clause will be required for each route
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* the result of above will get piped into a master function that build the final sql
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* the master function will need to be called to build the sql statements into files of the project
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route baseline
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----------------------------------------------------------------------------------------------------------------------------------------------------
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* forecast = baseline (copied verbatim from actuals and increment the dates) + diffs. if orders are canceled this will show up as differ to baseline
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* regular updates to baseline may be required to keep up with canceled/altered orders
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* copy some period of actual sales and increment all the dates to serve as a baseline forecast
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2020-10-30 01:19:55 -04:00
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2020-11-10 01:23:13 -05:00
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- [x] join to period tables to populate season; requires variance number oof table joins, based on howmany date functions there are 🙄
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2020-11-24 01:34:10 -05:00
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- [ ] some of the app parameters can be consolidated, the baseline period could be one large range potentially, instead of 2 stacked periods
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- [x] setup something to fill in sql parameters to do testing on the function
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- [ ] update node to handle forecast name parameter
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2020-11-28 02:17:53 -05:00
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- [ ] calc status is hard-coded right now in the json request -> probably needs to be manuall supplied up front
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2020-11-28 03:00:23 -05:00
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scale
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----------------------------------------------------------------------------------------------------------------------------------------------------
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2020-12-08 01:14:52 -05:00
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- [x] need to add version columns to all CTE's
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2020-12-02 02:44:12 -05:00
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- [ ] need to build log insert
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2020-12-08 01:02:50 -05:00
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- [x] Need to build where clause for scenario
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2020-11-08 22:30:15 -05:00
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running problem list
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----------------------------------------------------------------------------------------------------------------------------------------------------
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* baseline route
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2020-11-10 01:23:13 -05:00
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- [x] problem: how will the incremented order season get updated, adding an interval won't work
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2020-11-08 22:44:23 -05:00
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* a table fc.odate, has been built, but it is incomplete, a setup function filling in these date-keyed tables could be setup
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* if a table is date-keyed, fc.perd could be targeted to fill in the gaps by mapping the associated column names
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2020-11-10 01:23:13 -05:00
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- [x] problem: the target sales data has to map have concepts like order_date, and the application needs to know which col is order date
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2020-11-08 22:44:23 -05:00
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* add column called application hook
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- [ ] there is not currently any initial grouping to limit excess data from all the document# scenarios
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2020-11-28 03:00:23 -05:00
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* general
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- [ ] clean up SQL generation to prevent injection
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2020-12-08 01:06:06 -05:00
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- [ ] how to handle a target value adjustment, which currency is it in?
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2020-12-08 01:30:02 -05:00
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- [ ] **the sales data has to have a column for module and change ID, live sales data isn't going to work well**
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- [ ] need to target the live sales data, build build a whole new table to use it plus add version columns
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