I have an embedded h2 database in my server application. Our application generates large number of rows. For example, some tables will have 1 to 2 million rows in a day. Our application tries to persist the data to disk periodically just in case if a server crash happens. So far we tried using the Script function to persist each table to disk and when the server restarts, the data is reloaded using the runscript function. My question is:
What is the fastest way to load the data? for the same amount of data, does loading from an equivalent csv file faster than this way? The reason I am asking this is I saw in the documentation and it said it is similar to "bulk load". Also we found snapshot the entire table takes time, what we would like is be able to snapshot only the incremental changes. For this what we have done is we first snapshot the entire table to disk. As new data being put into the database, we also append this delta into the file. if when a server restarts, it will load this file again. When loading this data, how is the insert statements are being executed? Does each insert stmt being treated as a transaction? If I wrap a number of insert stmts within a begin and commit block, would this help increase loading speed? I also looked the script file generated by the script function. I saw many insert statements and each insert stmt has many data fields. But I can't tell how many records each insert stmt is actually inserting. Can someone please explain? Thank you in advance for your time and assistance. Jamie -- You received this message because you are subscribed to the Google Groups "H2 Database" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at http://groups.google.com/group/h2-database. For more options, visit https://groups.google.com/groups/opt_out.
