get_data very very slow to retrieve closing prices for R3000, daily, 13 years

HeikoRR

I followed the suggestion of Alex Putkov (https://community.developers.refinitiv.com/questions/57533/1-get-timeseries-cuts-off-historic-data-2-get-data.html) to split up the 3000 requests into chunks of 50 at a time using the code in "R" (not Python) below.

j=1

RIC.long = NULL

chunk = 30

for(i in c(seq(chunk,length(RIC), by=chunk),length(RIC))){

RIC.list = vector("list", length(RIC[j:i]))

RIC.list[1:length(RIC[j:i])] = RIC[j:i]

RIC.long = rbind(RIC.long,

get_data(RIC.list,

list( "TR.PriceClose.Date","TR.PriceClose"),

list("Frq"="D","SDate"=startDate,"EDate"="2020-04-09")))

j=i+1

}

Problem:

- It runs fine within 1 minute for startDate = "2020-04-01" - so a short history OK

- for startDate = "2005-01-01" in chunks of 30, it takes 33min (granted I am working from home with download = 14 Mbits/s and upload = 8 Mbits/s)

Question: Is this normal? On my Bloomberg R API it would have been a single request in under 1 min. I also tried to download it in a forloop RIC by RIC which takes about 60min. Chunk size of 50, throughs errors.

Thank you for possible insights, if this is the Eikon normal or if I am doing something wrong.

chavalit-jintamalit

I just tested iterating a list of RIC to retrieve 3000 data points on each RIC using Eikon Data API(Python)

It took me around 20 seconds to retrieve 3000 x 20 datapoints.

And around 120 seconds to retrieve 3000 x 100 datapoints.

So I would say that 3000 datapoint x 3000 RICs would require around 3000 seconds.

HeikoRR

Hi Chavalit,
You seem to confirm my findings.

Best regards