On 11/22/20 9:53 AM, Hagen Finley wrote:
Hello Michael,
Thanks so much for this advice. As I mentioned previously, I'm not very
good at this yet, so forgive me if my response is obtuse. I really love
databases but my sentiments may be unrequited.
The overriding issue is lack of a plan. From your first post:
"Here’s what I (REALLY) want:
Trigger looks at three fields prior to new insert: Deal ID (numeric),
revenue (numeric), stage(char) Example: 19743576 22072.37 Commit
- 90%
1. If the NEW dealid doesn't match any of the OLD dealids, insert the
new row
2. if the NEW dealid, revenue and stage fields ALL match the OLD
dealid, revenue and stage, skip (don't insert the NEW row)
3. If the NEW dealid matches an OLD dealid but either the NEW revenue
OR the stage fields have changed (don't match OLD record) insert new
row (I'll review both rows manually)
"
And from later post:
" I figure I could
use the chk field to delete the new inserts I didn't need."
From this I come up with the following:
1) Data rules
a) If dealid in new data does not exist in old data INSERT row.
b) Id dealid is in both new and old data AND revenue OR stage don't
match then INSERT and mark for review.
c) If new dealid, revenue, stage match old dealid, revenue, stage
then do not INSERT.
2) Process the data. Choices
a) Use trigger on table sfdc
b) Use staging table to hold new data and then process into sfdc table
3) Process the data. Same basic principle for both choices in 2) Flowchart
a) In new data search for dealid in table sfdc if it does not exist
add data to sfdc.
b) If new data dealid does exist in sfdc
1) If revenue or stage field differ mark for review
2) If they do match skip further processing
4) Thoughts about above.
a) To me table sfdc should only hold vetted data that is known to be
unique per row.
b) The data for review 1)b) 3)b) should end up in another review
table e.g. sfdc_review.
c) Since from OP ' 80% of the records are
the same as the existing records from the week before.' it makes sense
to use the staging table 2)b) process rather then throwing away a lot of
INSERTs.
If this makes sense then it comes down to decision in which choice in 2)
to use. At that point it is filling in the flowchart with the exact
steps to take.
In reality my table has lots of columns (~30) including a report date
(repdate) and each week's pull has a new repdate ( in this case
2020-11-02 and 2020-11-09) which could function as a "created on" field.
To clarify, I would create an unique index on all the columns in the old
report records (2020-11-02) or just the three I am comparing
(dealid,stage and revenue)?
In either case, so far in my efforts it looks like the create index
fails because there are lots of rows with the same stage value, and a
few with the same revenue value.
Create UNIQUE INDEX idx_sfdc
ON sfdc(ndealid, stage, revusd);
ERROR: could not create unique index "idx_sfdc" DETAIL: Key (ndealid,
stage, revusd)=(19743576, Commit - 90% , 22072.37) is duplicated. SQL
state: 23505
I probably could create an unique index on the dealid column as that
should be unique. Would that be enough? It seems like that would insert
ONLY the new records with a new (unique) dealid and that would
definitely by an important step forward.
I hesitate to admit I have no idea how I would code the "call insert on
conflict (unique index) do nothing" syntax, but I would be excited to learn.
Best,
Hagen
On 11/22/20 8:54 AM, Michael Lewis wrote:
If you can modify your insert statement, and live with an extra column
in the data, no trigger is needed as best I can figure.
Create a unique index over the existing columns, add a "created_on"
field and call insert on conflict (unique index) do nothing.
This should give the behavior you want.
--
Adrian Klaver
adrian.klaver@xxxxxxxxxxx
