Your questions are a little too vague to answer well, but let me try a bit.
1)In the query below , if the optimizer chooses tab1 as the driving table, the index on just col1 should be enough or it should be (col1, tab1_id)?
No way to tell without trying it yourself. We need information on how the tables are joined, the cardinality, general distribution, etc. But as a rough general rule, yes, indexes on the column of interest should be able to handle the job well by themselves.
2)In scenarios where the customer has a lot of matching transactions (say in millions) post all the filters applied , and as the customer has to just see the latest 100 rows transaction data, the sorting will be a bottleneck. So what can be done to make such types of queries to return the latest transactions in quick time on the search screen?
Sorting can be quick, if you hit an index (b-trees are already sorted) Postgres can look at only the first X rows returned and does not need to read the whole thing. So a well-designed index is the key here.
3)As here also the count has to happen in the first step to make the customer know the total number of rows(which may be in millions), so what additional index will support this requirement?
Again, a very vague question, but for things that are in millions, an estimate is usually sufficient, so you might be able to do something like SELECT count(*) FROM mytab WHERE mydate BETWEEN x AND y; and use that as your answer. Compare to the full query to see how close it is. You might even have cutoffs, where if the results of that first one is < 10,000, switch to a more accurate version which has more filtering (i.e. the joins and more where conditions).
Or if any other optimization strategy we can follow for catering to such queries?
select * from tab1, tab2
where tab1.part_date between '1-jan-2024' and '31-jan-2024'
and tab1.part_date=tab2.part_date
and tab1.tab1_id=tab2.tab2_id
and tab1.col1=<:input_col1>
and tab2.col2=<:input_col2>
order by tab1.create_timestamp desc
limit 100 offset 100;
It probably would help to see exact tables and queries. Why are you joining on part_date? Is tab_id unique to either table? Running EXPLAIN on these while you try out indexes and change the joins, etc. is a great exercise to help you learn how Postgres works. As far as asking on lists for help with specific queries, there is a range between totally abstract and generic queries that nobody can help you with, and large, complex specific queries that nobody wants to unravel and help you with. You are definitely on the former side: try to create some actually runable sample queries that are small, self-contained, and generate the problem you are trying to solve.
Cheers,
Greg