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Query idempotence

A query is idempotent if it can be applied multiple times without changing the result of the initial application. For example:

Idempotence matters for retries and speculative query executions . The driver will bypass those features if the Statement#isIdempotent() flag is set to false , to ensure that the statement does not get executed more than once.

In most cases, you must set that flag manually. The driver does not parse query strings, so it can’t infer it automatically (except for statements coming from the query builder, see below).

Statements start out as non-idempotent by default. You can override the flag on each statement:

The default is also configurable: if you want all statements to start out as idempotent, do this:

Any statement on which you didn’t call setIdempotent gets this default value.

Bound statements inherit the flag from the prepared statement they were created from:

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DSL tries to infer the isIdempotent flag on the statements it generates. The following statements will be marked non-idempotent :


counter updates:

prepend, append or deletion operations on lists:

queries that insert the result of a function call or a “raw” string in a column (or as an element in a collection column):

This is a conservative approach, since the driver can’t guess whether a function is idempotent, or what a raw string contains. It might yield false negatives, that you’ll have to fix manually.

lightweight transactions (see the next section for a detailed explanation):

If these rules produce a false negative, you can manually override the flag on the built statement:

As explained in the previous section, the query builder considers lightweight transactions as non-idempotent. This might sound counter-intuitive, as these queries can sometimes be safe to execute multiple times. For example, consider the following query:

If we execute it twice, the IF condition will fail the second time, so the second execution will do nothing and v will still have the value 4.

However, the problem appears when we consider multiple clients executing the query with retries:

One important aspect of lightweight transactions is linearizability : given a set of concurrent operations on a column from different clients, there must be a way to reorder them to yield a sequential history that is correct. From our clients’ point of view, there were two operations:

Marshal .to_bytesvflags returns a byte sequence containing the representation of v . The flags argument has the same meaning as for Marshal .to_channel .

Same as to_bytes but return the result as a string instead of a byte sequence.

Marshal .to_bufferbuffofslenvflags marshals the value v , storing its byte representation in the sequence buff , starting at index ofs , and writing at most len bytes. It returns the number of bytes actually written to the sequence. If the byte representation of v does not fit in len characters, the exception Failure is raised.

Marshal .from_channelchan reads from channel chan the byte representation of a structured value, as produced by one of the Marshal .to_* functions, and reconstructs and returns the corresponding value.

It raises End_of_file if the function has already reached the end of file when starting to read from the channel, and raises Failure "input_value:truncatedobject" if it reaches the end of file later during the unmarshalling.

Marshal .from_bytesbuffofs unmarshals a structured value like Marshal .from_channel does, except that the byte representation is not read from a channel, but taken from the byte sequence buff , starting at position ofs . The byte sequence is not mutated.

Same as from_bytes but take a string as argument instead of a byte sequence.

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buffofs is the size, in bytes, of the data part, assuming a valid header is stored in buff starting at position ofs . Finally, Marshal .total_size buffofs is the total size, in bytes, of the marshaled value. Both nike air max thea womens cross trainers black/grey
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raise Failure if buff , ofs does not contain a valid header.

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