Documentation ¶
Index ¶
- Variables
- func DoParallelQueries(ctx context.Context, doSingleQuery DoSingleQuery, queries []index.Query, ...) error
- func EnsureDirectory(dir string) error
- func GetParallelChunks(ctx context.Context, maxParallel int, chunks []chunk.Chunk, ...) ([]chunk.Chunk, error)
- func NewReadCloserWithContextCancelFunc(readCloser io.ReadCloser, cancel context.CancelFunc) io.ReadCloser
- type DoSingleQuery
- type ReadCloserWithContextCancelFunc
Constants ¶
This section is empty.
Variables ¶
var QueryParallelism = 100
QueryParallelism is the maximum number of subqueries run in parallel per higher-level query
Functions ¶
func DoParallelQueries ¶
func DoParallelQueries( ctx context.Context, doSingleQuery DoSingleQuery, queries []index.Query, callback index.QueryPagesCallback, ) error
DoParallelQueries translates between our interface for query batching, and indexes that don't yet support batching.
func EnsureDirectory ¶
EnsureDirectory makes sure directory is there, if not creates it if not
func GetParallelChunks ¶
func GetParallelChunks(ctx context.Context, maxParallel int, chunks []chunk.Chunk, f func(context.Context, *chunk.DecodeContext, chunk.Chunk) (chunk.Chunk, error)) ([]chunk.Chunk, error)
GetParallelChunks fetches chunks in parallel (up to maxParallel).
func NewReadCloserWithContextCancelFunc ¶
func NewReadCloserWithContextCancelFunc(readCloser io.ReadCloser, cancel context.CancelFunc) io.ReadCloser
Types ¶
type DoSingleQuery ¶
DoSingleQuery is the interface for indexes that don't support batching yet.
type ReadCloserWithContextCancelFunc ¶
type ReadCloserWithContextCancelFunc struct { io.ReadCloser // contains filtered or unexported fields }
ReadCloserWithContextCancelFunc helps with cancelling the context when closing a ReadCloser. NOTE: The consumer of ReadCloserWithContextCancelFunc should always call the Close method when it is done reading which otherwise could cause a resource leak.
func (ReadCloserWithContextCancelFunc) Close ¶
func (r ReadCloserWithContextCancelFunc) Close() error