Thank`s Allin!

Now it is obvious that the slow speed of dbnomicsá 0.4 with or without metadata is related to the fact that both are usingá same new API of dbnomics.
Same problem with the failed statement of aá single request as I just figured out: The installed version of dbnomics 0.4 needs a correct stated dataset. Monthly data like ECB/IRS/M.IT.L.L40.CI.0000.EUR.N.Z runs only with a monthly dataset and not with a quaterly dataset. My installed version of dbnomics 0.2 in gretl 2018c runs with both datasets without an error.


Am 29.03.2021 um 23:56 schrieb Allin Cottrell:
On Mon, 29 Mar 2021, wrote:

Thank you, Allin!

But I guess there is a bug in dbnonmics 0.4 with Windows 10. Bundle
requests via mask are slow as before (see for examble the attached scipt).

I see what you mean. Running a slightly cut-down version of your multi-series request, with mask "DEU+GBR+IAA..Q" and a maximum of 250 series, I'm seeing timings and JSON sizes as follows:

dbnomics 0.4, with metadata: 0m56.569s, 2317360 bytes
dbnomics 0.4, no metadata:áá 0m55.649s, 2296071 bytes

So cutting out the metadata makes little difference to the time or size. (Up till now we haven't been setting metadata=0 for this sort
of request -- we missed this case -- but it hardly helps.)

If I invoke the dbnomics v21 API instead, I get this:

time 0m4.886s, size 1905768 bytes

I still have to determine what's taking 10 times as long: dbnomics or gretl's processing of the data. But at this point my suspicion is that it's dbnomics.

And single requests such as

data ECB/IRS/M.IT.L.L40.CI.0000.EUR.N.Z are aborted immediatly with
"Keine Datenbank wurde ge÷ffnet"=no databank was opened

I'm not able to replicate that. I tried on Windows 10 today and the series arrived immediately.


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