Can a database table be without a primary key?

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谎友^
谎友^ 2021-01-31 14:39

Can anyone tell me if a table in a relational database (such as MySQL / SQL SERVER) can be without a primary key?

For example, I could have table day_temperature

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  • 2021-01-31 15:06

    When you replicate a database on mysql, A table without a primary key may cause delay in the replication.

    http://lists.mysql.com/mysql/227217

    The most common mistake when using ROW or MIXED is the failure to verify that every table you want to replicate has a PRIMARY KEY on it. This is a mistake because when a ROW event (such as the one documented above) is sent to the slave and neither the master's copy nor the slave's copy of the table has a PRIMARY KEY on the table, there is no way to easily identify which unique row you want replication to change.

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  • 2021-01-31 15:08

    If the possibility of having duplicate entries (for example for the same time) is not a problem, and you don't expect to have to query for specific records or range of records, you can do without any kind of key.

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  • 2021-01-31 15:08

    According to your answer I would consider three options:

    • put a PK on both cols, this way for each time there could be only one temp and vise versa. This solution allows for multiple rows with the same temp or the same time just that there wouldn't be any two rows with same temp AND time.
    • don't put a PK at all but do put a unique index on both cols. one unique index containing both cols. this would allow for nulls in temp and time but incurs more space to maintain index.

    these two options would be best for retrieval speed if you have heavy reads but would result in lower inserts rate as indices would have to be updated as well.

    • don't put any index at all, nor PK. this would be best for inserts but very bad for searching. useful for logging where retrieval is done by another mechanism or when inserting device is not required to check for dups.

    Also, it is very important to consider cardinality here and think about future consequences of using an auto incremented number. if you're planning to do A LOT OF inserts then even an auto incremented unsigned bigint would be a risk because it would eventually run out. In your example I guess you'll be saving data daily - for how long? this would be problematic if you saved temp every minute... so I'll take this as an extreme example.

    I guess it is best to think about what you need from the table. are you doing "save-and-forget" for the entire year for the temp at every minute? are you going to use this table frequently in real-time decision making in your business logic? I think it is best to segregate data necessary for real-time (oltp) from long-term saving data that would be required seldom and its retrieval latency is allowed to be high (olap). it's even worth duplicating the data into two different tables, one heavily indexed and get erased once in a while to control cardinality and the second is actually saved on a magentic disk with almost no indices at all (it is possible to transfer a schema from your main fs into another fs).

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  • 2021-01-31 15:14

    I run into the same question on one of the tables i did.

    The problem was that the PK was supposed to be composed out of all the rows of the table all is well but this means that the table size will grow very fast with each row inserted.

    I choose to not have a PK, but only have an index on the row i do the lookup on.

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  • 2021-01-31 15:15

    The time would then become your primary key. It will help index that column so that you can query data based on say a date range. The PK is what ultimately makes your row unique, so in your example, the datetime is the PK.

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  • 2021-01-31 15:18

    You don't need a PK, but it's recommended that you have one. It's the best way to identify unique rows. Sometimes you don't want an auto incremental int PK, but rather create the PK on something else. For example in your case, if there's only one unique row per time, you should create the PK on the time. It makes looks up based on time faster, plus it ensures that they're unique (you can be sure that the data integrity isn't violated):

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