![]() The write wear-out specs on SSDs and NVRAM devices generally are enough to heavily discourage patterns of usage that are not read-mostly. ![]() ![]() I would avoid your usage pattern purely for miserly reasons. However, given that spinning disks are often used in balanced read/write scenarios, a spinning disk buffering scheme might better support such a pattern than your SSD does.Ī side-note in case it is not obvious: I believe you are badly beating up that poor SSD. With a disk spinning (at 90+ revolutions/second), data fetching and data writing from/to separate tracks on the medium would likely be separated by movement of the flying head (aka "seeking") and waiting for the data to whirl around to underneath the head(s). To ship that database to users, you can include it as a flutter asset. Open the pubspec.yaml file and add the following line: dependencies: sqflite: '0.11. Of course, you can also create the database programmatically by using a library like sqlite3 (or even drift itself). Step 1: Importing sqflite You first need to start by importing sqflite plugin in your project. You can create a database with the sqlite3 CLI tool on your development machine. 1 Your initial results demonstrate (to me) that the buffering system in the SSD is doing very little good for transfer speed in your balanced read/write usage.ĭoes it matter that this is an SSD and not a spinning disk? First, create the sqlite3 database you want to ship with your app. I believe that SSDs are highly optimized for lots of reading and little writing. Use the insert () method to store the Map in the dogs table. This involves two steps: Convert the Dog into a Map. I would say the extra time was probably consumed getting data read out of the NVRAM devices when page reads within the SSD are largely going to waste because the SSD-level reads are interrupted by unrelated write operations. Now that you have a database with a table suitable for storing information about various dogs, it’s time to read and write data. (Referring to execution times becoming comparable during experiment:)ĭoes this mean that when I did it originally most of the time it took was lots of separate disk reads?
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