Instead of lengthy blurbs, switch to single-line, machine-readable
standardized (https://spdx.dev) license identifiers. The Linux kernel
switched long ago, so there is strong precedent.
Three cases are handled: AGPL-only, Apache-only, and dual licensed.
For the latter case, I chose (AGPL-3.0-or-later and Apache-2.0),
reasoning that our changes are extensive enough to apply our license.
The changes we applied mechanically with a script, except to
licenses/README.md.
Closes#9937
In some places we use the `*reinterpret_cast<const net::packed<T>*>(&x)`
pattern to reinterpret memory. This is a violation of C++'s aliasing rules,
which invokes undefined behaviour.
The blessed way to correctly reinterpret memory is to copy it into a new
object. Let's do that.
Note: the reinterpret_cast way has no performance advantage. Compilers
recognize the memory copy pattern and optimize it away.
Seastar recently lost support for the experimental Concepts Technical
Specification (TS) and gained support for C++20 concepts. Re-enable
concepts in Scylla by updating our use of concepts to the C++20
standard.
This change:
- peels off uses of the GCC6_CONCEPT macro
- removes inclusions of <seastar/gcc6-concepts.hh>
- replaces function-style concepts (no longer supported) with
equation-style concepts
- semicolons added and removed as needed
- deprecated std::is_pod replaced by recommended replacement
- updates return type constraints to use concepts instead of
type names (either std::same_as or std::convertible_to, with
std::same_as chosen when possible)
No attempt is made to improve the concepts; this is a specification
update only.
Message-Id: <20200531110254.2555854-1-avi@scylladb.com>
`linearizing_input_stream` allows transparently reading linearized
values from a fragmented buffer. This is done by linearizing on-the-fly
only those read values that happen to be split across multiple
fragments. This reduces the size of the largest allocation from the size
of the entire buffer (when the entire buffer is linearized) to the size
of the largest read value. This is a huge gain when the buffer contains
loads of small objects, and modest gains when the buffer contains few
large objects. But the even in the worst case the size of the largest
allocation will be less or equal compared to the case where the entire
buffer is linearized.
This stream is planned to be used as glue code between the fragmented
cell value and the collection deserialization code which expects to be
reading linearized values.
