size_t block_writer::write_block(size_t segment_id,
size_t column_id,
char* data,
block_info block) {
DASSERT_LT(segment_id, m_index_info.nsegments);
DASSERT_LT(column_id, m_index_info.columns.size());
DASSERT_TRUE(m_output_files[segment_id] != nullptr);
// try to compress the data
size_t compress_bound = LZ4_compressBound(block.block_size);
auto compression_buffer = m_buffer_pool.get_new_buffer();
compression_buffer->resize(compress_bound);
char* cbuffer = compression_buffer->data();
size_t clen = compress_bound;
clen = LZ4_compress(data, cbuffer, block.block_size);
char* buffer_to_write = NULL;
size_t buffer_to_write_len = 0;
if (clen < COMPRESSION_DISABLE_THRESHOLD * block.block_size) {
// compression has a benefit!
block.flags |= LZ4_COMPRESSION;
block.length = clen;
buffer_to_write = cbuffer;
buffer_to_write_len = clen;
} else {
// compression has no benefit! do not compress!
// unset LZ4
block.flags &= (~(size_t)LZ4_COMPRESSION);
block.length = block.block_size;
buffer_to_write = data;
buffer_to_write_len = block.block_size;
}
size_t padding = ((buffer_to_write_len + 4095) / 4096) * 4096 - buffer_to_write_len;
ASSERT_LT(padding, 4096);
// write!
m_output_file_locks[segment_id].lock();
block.offset = m_output_bytes_written[segment_id];
m_output_bytes_written[segment_id] += buffer_to_write_len + padding;
m_index_info.columns[column_id].segment_sizes[segment_id] += block.num_elem;
m_output_files[segment_id]->write(buffer_to_write, buffer_to_write_len);
m_output_files[segment_id]->write(padding_bytes, padding);
m_blocks[segment_id][column_id].push_back(block);
m_output_file_locks[segment_id].unlock();
m_buffer_pool.release_buffer(std::move(compression_buffer));
if (!m_output_files[segment_id]->good()) {
log_and_throw_io_failure("Fail to write. Disk may be full.");
}
return buffer_to_write_len;
}
void pysgraph_synchronize::load_vertex_partition(size_t partition_id, std::vector<sgraph_vertex_data>& vertices) {
DASSERT_LT(partition_id, m_num_partitions);
DASSERT_FALSE(m_is_partition_loaded[partition_id]);
m_vertex_partitions[partition_id] = std::move(vertices);
m_is_partition_loaded[partition_id] = true;
DASSERT_TRUE(is_loaded(partition_id));
}
/**
* Increments the value of a log entry
*/
void thr_dec_log_entry(size_t entry, double value) {
event_log_thread_local_type* ev = get_thread_counter_ref();
DASSERT_LT(entry, MAX_LOG_SIZE);
// does not work for cumulative logs
DASSERT_NE((int)logs[entry]->logtype, (int) log_type::CUMULATIVE);
DASSERT_EQ(logs[entry]->is_callback_entry, false);
ev->values[entry] -= value;
}
/// Return the next element in the chunk.
inline std::vector<flexible_type>&& sframe_reader_buffer::next() {
if (m_buffer_pos == m_buffer.size()) {
refill();
m_buffer_pos = 0;
}
DASSERT_LT(m_buffer_pos, m_buffer.size());
++m_iter;
return std::move(m_buffer[m_buffer_pos++]);
}
T&& sarray_reader_buffer<T>::next() {
if (m_buffer_pos == m_buffer.size()) {
refill();
m_buffer_pos = 0;
}
DASSERT_LT(m_buffer_pos, m_buffer.size());
++m_iter;
return std::move(m_buffer[m_buffer_pos++]);
}
/// Return the next element in the chunk.
inline const sframe_rows::row& sframe_reader_buffer::next() {
if (m_buffer_pos == m_buffer.num_rows()) {
refill();
m_buffer_pos = 0;
}
DASSERT_LT(m_buffer_pos, m_buffer.num_rows());
++m_iter;
m_current.copy_reference(m_buffer[m_buffer_pos++]);
return m_current;
}
void add(const T& t) {
// we use std::hash first, to bring it to a 64-bit number
// Then cityhash's hash64 twice to distribute the hash.
// empirically, one hash64 does not produce enough scattering to
// get a good estimate
size_t h = hash64(hash64(std::hash<T>()(t)));
size_t index = h >> (64 - m_b);
DASSERT_LT(index, m_buckets.size());
unsigned char pos = h != 0 ? 1 + __builtin_clz(h) : sizeof(size_t);
m_buckets[index] = std::max(m_buckets[index], pos);
}
static inline size_t get_bin_idx(
flexible_type value,
double scale_min,
double scale_max
) {
double range = scale_max - scale_min;
size_t bin = std::floor(
((static_cast<double>(value) - scale_min) / range) *
static_cast<double>(continuous_result::MAX_BINS)
);
if (bin == continuous_result::MAX_BINS) {
bin -= 1;
}
DASSERT_LT(bin, continuous_result::MAX_BINS);
return bin;
}
/**
* Create an SFrame parallel iterator.
*/
parallel_sframe_iterator::parallel_sframe_iterator(
const parallel_sframe_iterator_initializer& it_init, size_t thread_idx, size_t num_threads)
: sources(it_init.sources)
, column_offsets(it_init.column_offsets)
{
DASSERT_LT(thread_idx, num_threads);
buffers.resize(sources.size());
start_idx = it_init.row_start +
(thread_idx * it_init.global_block_size) / num_threads;
end_idx = it_init.row_start +
((thread_idx + 1) * it_init.global_block_size) / num_threads;
max_block_size = std::min(sframe_config::SFRAME_READ_BATCH_SIZE, end_idx - start_idx);
for(auto& b : buffers)
b.reserve(max_block_size);
reset();
}
// Add a new element to the specified bucket.
void add(const value_type& val, size_t bucketid) {
DASSERT_LT(bucketid, buckets.size());
buckets[bucketid]->add(val);
};
inline void load_vertex_partition(size_t partition_id, std::vector<sgraph_vertex_data>& vertices) {
DASSERT_LT(partition_id, m_num_partitions);
DASSERT_FALSE(m_is_partition_loaded[partition_id]);
m_vertex_partitions[partition_id] = &vertices;
m_is_partition_loaded[partition_id] = true;
}
inline bool is_loaded(size_t partition_id) {
DASSERT_LT(partition_id, m_num_partitions);
return m_is_partition_loaded[partition_id];
}
inline std::vector<sgraph_vertex_data>& get_partition(size_t partition_id) {
DASSERT_LT(partition_id, m_num_partitions);
DASSERT_TRUE(is_loaded(partition_id));
return m_vertex_partitions[partition_id];
}
/**
* Increments the value of a log entry
*/
inline void thr_inc_log_entry(size_t entry, double value) {
event_log_thread_local_type* ev = get_thread_counter_ref();
DASSERT_LT(entry, MAX_LOG_SIZE);
DASSERT_EQ(logs[entry]->is_callback_entry, false);
ev->values[entry] += value;
}
flexible_type operator()(const flexible_type& i) const{
DASSERT_LT(i, m_id_vec->size());
return m_id_vec->at(i);
}
