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is there an easy way to download the full nsc_dr2.object table?

I need to perform an all-sky query to then cross-match to Gaia QSOs, but with sql is taking very long and often crashes even if I do sub-queries and perform some cuts.

Thanks a lot,

asked Jul 13 by esacchi (120 points) | 160 views

1 Answer

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Hi Elena, thanks for reaching out. Downloading the entire nsc_dr2.object table will be difficult -- it's very big. We have done that on occasion, but for other institutions, and it required that they have access to Globus configured.

For your cross-match, would it help if you could use the pre-crossmatched table nsc_dr2.x1p5__object__gaia_dr2__gaia_source ? It's the xmatch of nsc_dr2.object against gaia_dr2.gaia_source, with a matching radius of 1.5 arcsec, keeping only the nearest match, and not keeping rows without a match. A JOIN operation on this table is much faster than a dedicated cross-match over the entire NSC DR2...


Other tips on cutting down the size in your queries:

- only request a few columns, not '*'

- experiment while using subqueries (as you do) and LIMIT statements

- go in slices of RA maybe?

Also, please feel free to send us a minimal workflow example that shows what you are trying to achieve, and where it fails. We will of course try to help. You can email to datalab@noirlab.edu

Best regards,

answered Jul 13 by robertdemo (2,340 points)
Thanks a lot for your quick reply.

I imagined that would be too much, so in the end I uploaded my table and used your online cross-match tool, which was surprisingly fast!

I thought about using nsc_dr2.x1p5__object__gaia_dr2__gaia_source but I also need magnitude columns, not only positions.

Thank you again,
Glad you got it to work.

The point / bonus of the pre-crossmatched tables is that one can then JOIN on either of the ID columns in those tables (which is much faster than cross-matching). So, you could use the pre-crossmatch tables to find the IDs you need, and then join on those IDs with other tables. Some examples are given in this notebook:



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