当您只需要几列时使用SELECT *意味着传输的数据比您需要的多得多。这增加了数据库上的处理，并增加了将数据获取到客户端的延迟。此外，它在加载时将使用更多内存，在某些情况下会使用更多内存，例如大型BLOB文件，这主要是关于效率。

然而，除此之外，在查看查询时更容易看到正在加载哪些列，而不必查找表中的内容。

是的，如果您确实添加了一个额外的列，它会更快，但在大多数情况下，您希望/需要使用查询更改代码以接受新列，并且有可能获得您不想要/期望的列会导致问题。例如，如果获取所有列，然后依赖循环中的顺序来分配变量，然后再添加一个，或者如果列的顺序发生了变化(从备份恢复时就发生过这种情况)，它可能会丢弃所有内容。

这也是为什么在执行INSERT操作时总是要指定列的原因。

有三个主要原因:

Inefficiency in moving data to the consumer. When you SELECT *, you're often retrieving more columns from the database than your application really needs to function. This causes more data to move from the database server to the client, slowing access and increasing load on your machines, as well as taking more time to travel across the network. This is especially true when someone adds new columns to underlying tables that didn't exist and weren't needed when the original consumers coded their data access. Indexing issues. Consider a scenario where you want to tune a query to a high level of performance. If you were to use *, and it returned more columns than you actually needed, the server would often have to perform more expensive methods to retrieve your data than it otherwise might. For example, you wouldn't be able to create an index which simply covered the columns in your SELECT list, and even if you did (including all columns [shudder]), the next guy who came around and added a column to the underlying table would cause the optimizer to ignore your optimized covering index, and you'd likely find that the performance of your query would drop substantially for no readily apparent reason. Binding Problems. When you SELECT *, it's possible to retrieve two columns of the same name from two different tables. This can often crash your data consumer. Imagine a query that joins two tables, both of which contain a column called "ID". How would a consumer know which was which? SELECT * can also confuse views (at least in some versions SQL Server) when underlying table structures change -- the view is not rebuilt, and the data which comes back can be nonsense. And the worst part of it is that you can take care to name your columns whatever you want, but the next guy who comes along might have no way of knowing that he has to worry about adding a column which will collide with your already-developed names.

但这对SELECT *来说也不全是坏事。我在以下用例中大量使用它:

Ad-hoc queries. When trying to debug something, especially off a narrow table I might not be familiar with, SELECT * is often my best friend. It helps me just see what's going on without having to do a boatload of research as to what the underlying column names are. This gets to be a bigger "plus" the longer the column names get. When * means "a row". In the following use cases, SELECT * is just fine, and rumors that it's a performance killer are just urban legends which may have had some validity many years ago, but don't now: SELECT COUNT(*) FROM table; in this case, * means "count the rows". If you were to use a column name instead of * , it would count the rows where that column's value was not null. COUNT(*), to me, really drives home the concept that you're counting rows, and you avoid strange edge-cases caused by NULLs being eliminated from your aggregates. Same goes with this type of query: SELECT a.ID FROM TableA a WHERE EXISTS ( SELECT * FROM TableB b WHERE b.ID = a.B_ID); in any database worth its salt, * just means "a row". It doesn't matter what you put in the subquery. Some people use b's ID in the SELECT list, or they'll use the number 1, but IMO those conventions are pretty much nonsensical. What you mean is "count the row", and that's what * signifies. Most query optimizers out there are smart enough to know this. (Though to be honest, I only know this to be true with SQL Server and Oracle.)

我不认为这真的可以有一个通用的规则。在许多情况下，我避免使用SELECT *，但我也使用过SELECT *非常有用的数据框架。

和所有事情一样，有收益也有成本。我认为收益与成本的等式的一部分是你对数据结构有多少控制。在SELECT *工作良好的情况下，数据结构受到严格控制(它是零售软件)，因此没有太大的风险，有人会将一个巨大的BLOB字段发送到表中。

如果您真的想要每个列，我没有看到select(*)和命名列之间的性能差异。命名列的驱动程序可能只是为了明确您希望在代码中看到哪些列。

但是，通常情况下，您不希望每个列和select(*)会导致数据库服务器做不必要的工作，并且必须通过网络传递不必要的信息。它不太可能造成明显的问题，除非系统被大量使用或网络连接很慢。

还有一个更实际的原因:钱。当你使用云数据库时，你必须为数据处理付费，没有任何解释来读取你将立即丢弃的数据。

例如:BigQuery:

查询价格 查询定价是指运行SQL命令和用户定义函数的成本。BigQuery根据一个指标对查询收费:处理的字节数。

和控制投影-避免选择*:

最佳实践:控制投影—只查询所需的列。 投影指的是查询读取的列数。投影多余的列会导致额外的(浪费的)I/O和物化(写入结果)。 使用SELECT *是最昂贵的查询数据的方法。当您使用SELECT *时，BigQuery会对表中的每一列进行全面扫描。

If you name the columns in a SELECT statement, they will be returned in the order specified, and may thus safely be referenced by numerical index. If you use "SELECT *", you may end up receiving the columns in arbitrary sequence, and thus can only safely use the columns by name. Unless you know in advance what you'll be wanting to do with any new column that gets added to the database, the most probable correct action is to ignore it. If you're going to be ignoring any new columns that get added to the database, there is no benefit whatsoever to retrieving them.