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Request strategy
Table 2 - Summary
Dataset |
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API field limits |
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Downloaded data size | Request strategy | Link to example script |
---|---|---|
GloFAS climatology |
500 | 2 GB | Loop over years |
GloFAS forecast |
60 | 8.1 GB | loop over years, months, days |
GloFAS |
reforecast | 950 | 32 GB | loop over months, days Subset to ROI |
GloFAS seasonal forecast |
125 | 31.5 GB | Loop over years, months Subset to ROI |
GloFAS |
seasonal |
reforecast | 125 | 31.5 GB | Loop over years, months Subset to ROI |
EFAS climatology |
1000 | to be confirmed | to be confirmed | to be confirmed | |
EFAS |
forecast | 1000 | to be confirmed | to be confirmed | to be confirmed |
EFAS reforecast |
200 | to be confirmed | to be confirmed | to be confirmed |
EFAS seasonal forecast |
220 | to be confirmed | to be confirmed | to be confirmed |
EFAS |
seasonal |
reforecast | 220 | to be confirmed | to be confirmed | to be confirmed |
Speed up retrieval through concurrency:
The CDS enforces a per user limit to the number of requests that can be processed in parallel. This limit is 10 parallel requests running at the same time. The are also 'global limits' that can affect the user requests. More information here.
Whilst submitting multiple requests can improve the tasks' index in the queuing system, the user needs to understand that download time, overloading the system with too many requests will eventually slow down the overall system performance.
Indeed the CDS system penalises users that submit too many requests, decreasing the priority of their requests.
Too many parallel requests could eventually result in a slower overall download time
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