Mysql boolean field9/10/2023 UUIDs are horrible for large tables due to the randomness of accessing - hence high I/O.Set innodb_buffer_pool_size to about 70% of RAM size.(Note: If the subpartitioning can be made to work this index is not needed.) Do it hourly (or continually) so that the delete is not to bigĪlso, have INDEX(IsDirty, CreatedOn) - in this order.If you do end up with a big DELETE every night, then either This may work, and may allow for DROP PARTITION, but I am baffled as to the syntax. You would not be able to use DROP PARTITION, which would make the deletion very fast. Anyway, you would need to have a growing number of partitions and use PARTITION BY RANGE(to_days(.)). I think I've read somewhere a reason for this, but I've forgotten about it).ĭon't bother with partitioning, it is unlikely to help performance. There is a bool datatype (which is internally realised as tinyint(1). The optimizer now is more complex and bases its estimate on additional factors such as table size, number of rows, and I/O block size.Īlso note, that the bit datatype is not ideal to store values 0 or 1. At one time, a scan was used based on whether the best index spanned more than 30% of the table, but a fixed percentage no longer determines the choice between using an index or a scan. The manual states the following about when a full table scan is prefered:Įach table index is queried, and the best index is used unless the optimizer believes that it is more efficient to use a table scan. Your delete job on the other hand, which checks for IsDirty = 0 would not benefit, as it's cheaper to simply do a full table scan, because using a secondary index means, that from the index the primary key is read (in every secondary index the primary key is stored, therefore it's always good to make the primary key as small as possible) to identify the row to be read. When only 10% have IsDirty = 1, queries like select * from your_table where IsDirty = 1 would benefit from the index. However this does not consider the distribution of the data. When you do a show indexes from your_table you would see, that your IsDirty column has a cardinality of 2. Cardinality is the estimated number of distinct values in the column. Seems like Alembic can't see the changes in the model.There is a rule of thumb which says, that it's best to index columns with a high cardinality. from import BOOLEANĪnd still I get the same error when flask run migrate. But reading this Github thread I understand that the Boolean class will turn into TINYINT based on the dialect. Reading MySQL documentation found out that MySQL doesn't have boolean type rather TINYINT. Invited = db.Column(BOOLEAN, default=0) # also with Booleanīut get the same error. I also tried from sqlalchemy import BOOLEAN # also with Boolean invited = db.Column(db.Boolean, default=0)īut when I runt flask db migrate I get the following. Now I want to add a new boolean column to the model. Patterns = db.relationship('Pattern', backref='user', lazy='dynamic') Password_hash = db.Column(db.String(128)) Username = db.Column(db.String(64), index=True, unique=True)Įmail = db.Column(db.String(128), index=True, unique=True) Id = db.Column(db.Integer, primary_key=True) I have a working flask app with few models.
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