what is the correct expression for this: SELECT e....
# ask-stanley-ai
n
what is the correct expression for this: SELECT e.id FROM transaction t JOIN transactionLine tl ON t.id = tl.transaction JOIN department d ON tl.department = d.id JOIN account a on tl.expenseaccount = a.id JOIN vendor v on t.entity = v.id JOIN vendorCategory c on v.category = c.id JOIN employee e ON d.custrecord_sw_dept_corp_approver = e.id WHERE t.id = '3045190' AND v.id != '513' AND c.id IS NOT NULL AND c.id != '7' AND ( tl.linesequencenumber = 0 AND a.custrecord_sw_account_approver IS NULL AND tl.custcol_cs_vbill_item_exception IS NULL )
c
AI generated answer (using internal Slack threads):
The provided SQL query is correct as it is. It is a complex SQL query that joins multiple tables based on their relationships and filters the data based on certain conditions. Here is a brief explanation of the query: 1. It selects the
id
from the
employee
table. 2. It joins the
transaction
table with the
transactionLine
table on the
id
field. 3. It further joins the
department
,
account
,
vendor
,
vendorCategory
, and
employee
tables based on their respective relationships. 4. It applies a filter condition on the
transaction
id,
vendor
id,
vendorCategory
id,
transactionLine
sequence number,
account
approver, and
transactionLine
item exception. If you are using NetSuite, you can use SuiteQL or SuiteScript to execute this SQL query. However, please note that the actual field names and join conditions may vary based on your NetSuite setup. ****** Disclaimer: This response was generated by an artificial intelligence assistant based on previous conversations from multiple Slack channels, and may contain inaccuracies or mistakes. ******
Slack thread 1: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.842825711
Slack thread 2: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.811751783
Slack thread 3: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.807300866
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