Hello! There's no way you will load 20,000 records in 25 minutes. That's 10 records per second. I just can't think of any reason why it might take such monumental amount of time.
With regards to data streamer, as I have said I recommend partitioning your data and loading every segment from its own thread, using shared data streamer instance. Regards, -- Ilya Kasnacheev вт, 18 февр. 2020 г. в 20:14, nithin91 < [email protected]>: > Hi > > We are doing POC, as a result of which we are running it in local mode. > > Currently it is taking 25min to load 20000 records with Cache JDBC POJO > Store. > > Even i am giving the initial filter to reduce unnecessary records. > > > > > ignite.cache("PieProductRiskCache").loadCache(null,"ignite.example.IgniteUnixImplementation.PieProductRiskKey", > "select * from Table where > as_of_Date_Std='31-Dec-2019'"); > > Regarding the Data Steamer code i have shared, is that the way we implement > Data Steamers or is there another way of implementing Data Steamers.If the > approach is correct, then it will not not work right as we are looping > through the result set. > > > > -- > Sent from: http://apache-ignite-users.70518.x6.nabble.com/ >
