Yahoo-Finance Query Speed

Question

I'm currently working on a project that involves querying yahoo-finance for many different ticker symbols. The bottleneck is acquiring the data from yahoo, so I was wondering if there is a way I might go about speeding this up.

If I used multiple machines to query and then aggregated the data, would that help? I only have one physical machine; how might I go about doing that?

Thanks!

EDIT: Currently, I'm using Node.js, yahoo-finance, and Q.deferred to ask yahoo for historical data. Then, once all the promises are fulfilled (for each ticker), I'm doing a Q.all() to persist the data.

    var data = [];
    tickers = ["goog", "aapl", ...];
    ...
    Q.all(_.map(tickers, function(symbol) { 
        return getYahooPromise(symbol);
     }))
    .done( function() { persistData(data) });

getYahooPromise retrieves data for the ticker symbol and pushes it into the data array. Once all promises are resolved, the data is persisted in a MySQL database.

SECOND EDIT: More code:

var sequentialCalls = [];

for ( var i = 0; i < tickers.length / chunkSize; i++ ) {
    sequentialCalls.push( persistYahooChunk );
}
sequentialCalls.push( function(callback) { 
    connection.end(); 
    callback();
});

async.series( sequentialCalls )



exports.persistYahooChunk = function(callback) {
console.log("Starting yahoo query");
var currentTickers = tickers.slice(currentTickerIndex,currentTickerIndex + chunkSize);


return yahooFinance.historical( {
    symbols: currentTickers,
    from: "2015-01-28",
    to: "2015-02-05"
}).then( function(result) {
    console.log("Query " + currentTickerIndex +  "/" + tickers.length + "completed");
    currentTickerIndex += chunkSize;
    //add valid data
    var toPersist = _.map(result, function(quotes, symbol) {
            return [symbol, quotes.length != 0 ];
    });


    var query = "INSERT INTO `ticker` (`symbol`, `valid`) VALUES ?";
    connection.query(query, [toPersist], function(err, result) {
        if (err) {
            console.log (err);
        }
        //console.log(result);

        callback();
    });
});

}

Answer 1

The bottleneck is because you are doing one query per ticker.

Depending on the data you need to pull, if you could do a single query that includes all your tickers it would be much faster.

Here is an example if you need to get all current prices for a list of tickers, with a single query :

http://finance.yahoo.com/webservice/v1/symbols/A,B,C,D,E/quote?format=json