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#ifndef TENSORFLOW_LIB_IO_TABLE_OPTIONS_H_
#define TENSORFLOW_LIB_IO_TABLE_OPTIONS_H_
#include <stddef.h>
namespace tensorflow {
namespace table {
// DB contents are stored in a set of blocks, each of which holds a
// sequence of key,value pairs. Each block may be compressed before
// being stored in a file. The following enum describes which
// compression method (if any) is used to compress a block.
enum CompressionType {
// NOTE: do not change the values of existing entries, as these are
// part of the persistent format on disk.
kNoCompression = 0x0,
kSnappyCompression = 0x1
};
// Options to control the behavior of a table (passed to Table::Open)
struct Options {
// Approximate size of user data packed per block. Note that the
// block size specified here corresponds to uncompressed data. The
// actual size of the unit read from disk may be smaller if
// compression is enabled. This parameter can be changed dynamically.
size_t block_size = 262144;
// Number of keys between restart points for delta encoding of keys.
// This parameter can be changed dynamically. Most clients should
// leave this parameter alone.
int block_restart_interval = 16;
// Compress blocks using the specified compression algorithm. This
// parameter can be changed dynamically.
//
// Default: kSnappyCompression, which gives lightweight but fast
// compression.
//
// Typical speeds of kSnappyCompression on an Intel(R) Core(TM)2 2.4GHz:
// ~200-500MB/s compression
// ~400-800MB/s decompression
// Note that these speeds are significantly faster than most
// persistent storage speeds, and therefore it is typically never
// worth switching to kNoCompression. Even if the input data is
// incompressible, the kSnappyCompression implementation will
// efficiently detect that and will switch to uncompressed mode.
CompressionType compression = kSnappyCompression;
};
} // namespace table
} // namespace tensorflow
#endif // TENSORFLOW_LIB_IO_TABLE_OPTIONS_H_
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