Transferring Large Data From Server to Client

Community Support
1

I am trying to implement a function to load large chunks of data, let’s say 1 billion rows, and load it into my local KDB+ instance. So far here is what I have:

\d .importer

fetch_data:{[table_names;batch_size;data_date]

    / (0) Open remote connection

    h::hopen `$“:redacted:redacted:redacted”;

    

    / (1) Set arguments

    tabs:enlist table_names;

    bsize::batch_size;

    dday::data_date;

    

    / (2) Create tables

    { .[x;();:;()] } each tabs;

    

    / (3) For each remote table;

    /     (3.1) Get the table count

    /     (3.2) Split the table to an optimal value

    /     (3.4) Iterate over the table by using the splits

    {[tab]

      tcount:h({[t;d] count select from t where date=d};tab;dday);

      splits:$[tcount>bsize; [batch:tcount div bsize;((0;bsize-1)+/:bsize*til batch),enlist (batch*bsize;tcount-1)];enlist(0;tcount-1)];

      {[t;dday;split] t upsert h({[t;y;dday] ?[t;((=;date;dday);(within;i;y));0b;()]};t;split;dday) }[tab;dday] each splits;

    }each tabs;

  }

fetch_today:fetch_data[;;.z.d];

fetch_quotes_today:fetch_data[`trades;;.z.d];

fetch_quotes:fetch_data[`trades;;];

Then I simply load the script and call, let’s say,

.importer.fetch_quotes_today[1000000]

..and it works fine if there is 40-50 million data tops. But if the rows count exceeds 100M then the execution takes forever. Now that I have about a billion data rows, is there any more effective way to transfer such data directly from KDB to KDB?

Regards!

2

Sounds like you are running out of memory. 
Glancing at the script, it looks like you upsert in memory. You could upsert on disk. 

3

Well, I didn’t face any OOM or Swap Memory issues nor alarms in monitoring, thank you for your suggestion. I’ll try to persist directly on disk and see!

4

Would it not make more sense to scp or rsync in this type of scenario?

5

As @wp suggested, I switched to upsert asynchronously into a file directly and it seems working fine now! Below you can find the updated snippet:

…

…

/ (1) Set arguments

    tabs:enlist table_names;

    bsize::batch_size;

    dday::data_date;

    

    / (2) Create tables

    { .[x;();:;()] } each tabs;

    

    / (3) For each remote table;

    /     (3.1) Get the table count

    /     (3.2) Split the table to an optimal value

    /     (3.3) Fetch the meta to create a proper CSV

    /     (3.4) Open file handle

    /     (3.5) Iterate over the table by using the splits and for each batch

    /           (3.5.1) Asynchronously save data to the CSV file

    {[tab]

      tcount:h({[t;d] count select from t where date=d};tab;dday);

      splits:$[tcount>bsize; [batch:tcount div bsize;((0;bsize-1)+/:bsize*til batch),enlist (batch*bsize;tcount-1)];enlist(0;tcount-1)];

      tmeta: key h({[t] meta t};tab);         

      (hsym `$ raze string tab,“.csv”) 0: enlist “,” sv raze string flip tmeta cols tmeta;

      fhandle:hopen (hsym `$ raze string tab,“.csv”);      

      {[t;dday;tcount;fhandle;split] 

        neg[fhandle] peach “,” 0:h({[t;y;dday] ?[t;((=;date;dday);(within;i;y));0b;()]};t;split;dday); 

        show raze string split[0],“-”,split[1]," of ", tcount; }[tab;dday;tcount;fhandle] each splits;

      hclose fhandle; 

    }each tabs;

    hclose h;

…

…

Thanks for the advice!

Regards @wp and @Morten.