My database consists of 12 tables, and I'm executing 2 queries. The first one joins 10 of the tables, and the second one joins 2 of the remaining tables. Most of the tables are very small (2-4 columns, approx. 50 records). One table is about 200 records and the largest table (involved in the first query) is about 10,000 records. The .mv.db file size is approx. 300KB.
When I run the 2 queries in the normal (embedded/on-disk) way, it takes an average of about 25ms (Macbook ~2015 8GB i5 2.4GX2). When I run it in-memory, it takes about the same. Actually, initially I was running it without a primary hash key and the results were worse. Now, with the primary hash keys, they have the same performance. I made sure I added DB_CLOSE_DELAY=-1 to my connection string for the in-memory version. Besides the DB_CLOSE_DELAY and the primary hash keys, am I missing any performance optimization techniques? TIA, Tiberiu -- 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 https://groups.google.com/group/h2-database. For more options, visit https://groups.google.com/d/optout.
