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Adding MAP type support for ORC Reader #9132

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merged 27 commits into from
Sep 9, 2021
Merged

Adding MAP type support for ORC Reader #9132

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code changes and test cases
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Merge branch 'branch-21.08' of https://github.com/rapidsai/cudf into …
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Fixes for pyspark generated orc file reading
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Merge github.com:rapidsai/cudf into orc_struct_null_issue
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Merge branch 'branch-21.10' of github.com:rapidsai/cudf into orc_map_…
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Merge branch 'branch-21.10' of github.com:rapidsai/cudf into orc_map_…
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Merge branch 'branch-21.10' of github.com:rapidsai/cudf into orc_map_…
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using alias, created a function to fetch name for map child column na…
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Update cpp/src/io/orc/reader_impl.cu
rgsl888prabhu Sep 8, 2021
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97 changes: 70 additions & 27 deletions cpp/src/io/orc/reader_impl.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -79,6 +79,8 @@ constexpr type_id to_type_id(const orc::SchemaType& schema,
// There isn't a (DAYS -> np.dtype) mapping
return (use_np_dtypes) ? type_id::TIMESTAMP_MILLISECONDS : type_id::TIMESTAMP_DAYS;
case orc::DECIMAL: return (decimals_as_float64) ? type_id::FLOAT64 : type_id::DECIMAL64;
// Need to update once cuDF plans to support map type
case orc::MAP:
case orc::LIST: return type_id::LIST;
case orc::STRUCT: return type_id::STRUCT;
default: break;
Expand Down Expand Up @@ -490,20 +492,15 @@ class aggregate_orc_metadata {
const int col_id = selection[level].size() - 1;
if (types[id].kind == orc::TIMESTAMP) { has_timestamp_column = true; }

switch (types[id].kind) {
case orc::LIST:
case orc::STRUCT: {
has_nested_column = true;
for (const auto child_id : types[id].subtypes) {
// Since nested column needs to be processed before its child can be processed,
// child column is being added to next level
add_column(
selection, types, level + 1, child_id, has_timestamp_column, has_nested_column);
}
selection[level][col_id].num_children = types[id].subtypes.size();
} break;

default: break;
if (types[id].kind == orc::MAP or types[id].kind == orc::LIST or
types[id].kind == orc::STRUCT) {
has_nested_column = true;
for (const auto child_id : types[id].subtypes) {
// Since nested column needs to be processed before its child can be processed,
// child column is being added to next level
add_column(selection, types, level + 1, child_id, has_timestamp_column, has_nested_column);
}
selection[level][col_id].num_children = types[id].subtypes.size();
}
}

Expand Down Expand Up @@ -958,6 +955,8 @@ void reader::impl::aggregate_child_meta(cudf::detail::host_2dspan<gpu::ColumnDes
});
}

std::string get_map_child_col_name(size_t idx) { return (idx == 0) ? "key" : "value"; }
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std::unique_ptr<column> reader::impl::create_empty_column(const int32_t orc_col_id,
column_name_info& schema_info,
rmm::cuda_stream_view stream)
Expand All @@ -972,9 +971,10 @@ std::unique_ptr<column> reader::impl::create_empty_column(const int32_t orc_col_
int32_t scale = 0;
std::vector<std::unique_ptr<column>> child_columns;
std::unique_ptr<column> out_col = nullptr;
auto kind = _metadata->get_col_type(orc_col_id).kind;

switch (type) {
case type_id::LIST:
switch (kind) {
case orc::LIST:
schema_info.children.emplace_back("offsets");
schema_info.children.emplace_back("");
out_col = make_lists_column(
Expand All @@ -985,10 +985,30 @@ std::unique_ptr<column> reader::impl::create_empty_column(const int32_t orc_col_
0,
rmm::device_buffer{0, stream},
stream);

break;

case type_id::STRUCT:
case orc::MAP: {
schema_info.children.emplace_back("offsets");
schema_info.children.emplace_back("struct");
const auto child_column_ids = _metadata->get_col_type(orc_col_id).subtypes;
for (size_t idx = 0; idx < _metadata->get_col_type(orc_col_id).subtypes.size(); idx++) {
auto& children_schema = schema_info.children.back().children;
children_schema.emplace_back("");
child_columns.push_back(create_empty_column(
child_column_ids[idx], schema_info.children.back().children.back(), stream));
auto name = get_map_child_col_name(idx);
children_schema[idx].name = name;
}
auto struct_col =
make_structs_column(0, std::move(child_columns), 0, rmm::device_buffer{0, stream}, stream);
out_col = make_lists_column(0,
make_empty_column(data_type(type_id::INT32)),
std::move(struct_col),
0,
rmm::device_buffer{0, stream},
stream);
} break;

case orc::STRUCT:
for (const auto col : _metadata->get_col_type(orc_col_id).subtypes) {
schema_info.children.emplace_back("");
child_columns.push_back(create_empty_column(col, schema_info.children.back(), stream));
Expand All @@ -997,8 +1017,10 @@ std::unique_ptr<column> reader::impl::create_empty_column(const int32_t orc_col_
make_structs_column(0, std::move(child_columns), 0, rmm::device_buffer{0, stream}, stream);
break;

case type_id::DECIMAL64:
scale = -static_cast<int32_t>(_metadata->get_types()[orc_col_id].scale.value_or(0));
case orc::DECIMAL:
if (type == type_id::DECIMAL64) {
scale = -static_cast<int32_t>(_metadata->get_types()[orc_col_id].scale.value_or(0));
}
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Does this need to throw an exception if type == type_id::DECIMAL32?

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In case of orc:Decimal, there are chances where they expect us to return Double. And orc supports only Decimal64 and Decimal128 if I am not wrong.

out_col = make_empty_column(data_type(type, scale));
break;

Expand All @@ -1011,20 +1033,40 @@ std::unique_ptr<column> reader::impl::create_empty_column(const int32_t orc_col_
// Adds child column buffers to parent column
column_buffer&& reader::impl::assemble_buffer(const int32_t orc_col_id,
std::vector<std::vector<column_buffer>>& col_buffers,
const size_t level)
const size_t level,
rmm::cuda_stream_view stream)
{
auto const col_id = _col_meta.orc_col_map[level][orc_col_id];
auto& col_buffer = col_buffers[level][col_id];

col_buffer.name = _metadata->get_column_name(0, orc_col_id);
switch (col_buffer.type.id()) {
case type_id::LIST:
case type_id::STRUCT:
auto kind = _metadata->get_col_type(orc_col_id).kind;
switch (kind) {
case orc::LIST:
case orc::STRUCT:
for (auto const& col : _metadata->get_col_type(orc_col_id).subtypes) {
col_buffer.children.emplace_back(assemble_buffer(col, col_buffers, level + 1));
col_buffer.children.emplace_back(assemble_buffer(col, col_buffers, level + 1, stream));
}

break;
case orc::MAP: {
std::vector<column_buffer> child_col_buffers;
// Get child buffers
for (size_t idx = 0; idx < _metadata->get_col_type(orc_col_id).subtypes.size(); idx++) {
auto name = get_map_child_col_name(idx);
auto col = _metadata->get_col_type(orc_col_id).subtypes[idx];
child_col_buffers.emplace_back(assemble_buffer(col, col_buffers, level + 1, stream));
child_col_buffers.back().name = name;
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}
// Create a struct buffer
auto num_rows = child_col_buffers[0].size;
auto struct_buffer =
column_buffer(cudf::data_type(type_id::STRUCT), num_rows, false, stream, _mr);
struct_buffer.children = std::move(child_col_buffers);
struct_buffer.name = "struct";

col_buffer.children.emplace_back(std::move(struct_buffer));
} break;

default: break;
}
Expand All @@ -1043,7 +1085,7 @@ void reader::impl::create_columns(std::vector<std::vector<column_buffer>>&& col_
std::back_inserter(out_columns),
[&](auto const col_meta) {
schema_info.emplace_back("");
auto col_buffer = assemble_buffer(col_meta.id, col_buffers, 0);
auto col_buffer = assemble_buffer(col_meta.id, col_buffers, 0, stream);
return make_column(col_buffer, &schema_info.back(), stream, _mr);
});
}
Expand Down Expand Up @@ -1132,6 +1174,7 @@ table_with_metadata reader::impl::read(size_type skip_rows,

// Map each ORC column to its column
_col_meta.orc_col_map[level][col.id] = column_types.size() - 1;
// TODO: Once MAP type is supported in cuDF, update this for MAP as well
if (col_type == type_id::LIST or col_type == type_id::STRUCT) nested_col.emplace_back(col);
}

Expand Down
3 changes: 2 additions & 1 deletion cpp/src/io/orc/reader_impl.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -176,7 +176,8 @@ class reader::impl {
*/
column_buffer&& assemble_buffer(const int32_t orc_col_id,
std::vector<std::vector<column_buffer>>& col_buffers,
const size_t level);
const size_t level,
rmm::cuda_stream_view stream);
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Should this have a default, or will we always be calling it internally with a stream?

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Yes, this is only for internal use only.


/**
* @brief Create columns and respective schema information from the buffer.
Expand Down
28 changes: 17 additions & 11 deletions cpp/src/io/orc/stripe_data.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -1572,9 +1572,10 @@ __global__ void __launch_bounds__(block_size)
__syncthreads();
// Account for skipped values
if (num_rowgroups > 0 && !s->is_string) {
uint32_t run_pos = (s->chunk.type_kind == DECIMAL || s->chunk.type_kind == LIST)
? s->top.data.index.run_pos[CI_DATA2]
: s->top.data.index.run_pos[CI_DATA];
uint32_t run_pos =
(s->chunk.type_kind == DECIMAL || s->chunk.type_kind == LIST || s->chunk.type_kind == MAP)
? s->top.data.index.run_pos[CI_DATA2]
: s->top.data.index.run_pos[CI_DATA];
numvals =
min(numvals + run_pos, (s->chunk.type_kind == BOOLEAN) ? blockDim.x * 2 : blockDim.x);
}
Expand All @@ -1587,7 +1588,7 @@ __global__ void __launch_bounds__(block_size)
numvals = Integer_RLEv2(&s->bs, &s->u.rlev2, s->vals.i32, numvals, t);
}
__syncthreads();
} else if (s->chunk.type_kind == LIST) {
} else if (s->chunk.type_kind == LIST or s->chunk.type_kind == MAP) {
if (is_rlev1(s->chunk.encoding_kind)) {
numvals = Integer_RLEv1<uint64_t>(&s->bs2, &s->u.rlev1, s->vals.u64, numvals, t);
} else {
Expand Down Expand Up @@ -1676,15 +1677,17 @@ __global__ void __launch_bounds__(block_size)
} else {
vals_skipped = 0;
if (num_rowgroups > 0) {
uint32_t run_pos = (s->chunk.type_kind == LIST) ? s->top.data.index.run_pos[CI_DATA2]
: s->top.data.index.run_pos[CI_DATA];
uint32_t run_pos = (s->chunk.type_kind == LIST or s->chunk.type_kind == MAP)
? s->top.data.index.run_pos[CI_DATA2]
: s->top.data.index.run_pos[CI_DATA];
if (run_pos) {
vals_skipped = min(numvals, run_pos);
numvals -= vals_skipped;
__syncthreads();
if (t == 0) {
(s->chunk.type_kind == LIST) ? s->top.data.index.run_pos[CI_DATA2] = 0
: s->top.data.index.run_pos[CI_DATA] = 0;
(s->chunk.type_kind == LIST or s->chunk.type_kind == MAP)
? s->top.data.index.run_pos[CI_DATA2] = 0
: s->top.data.index.run_pos[CI_DATA] = 0;
}
}
}
Expand Down Expand Up @@ -1720,6 +1723,7 @@ __global__ void __launch_bounds__(block_size)
case DECIMAL:
static_cast<uint64_t*>(data_out)[row] = s->vals.u64[t + vals_skipped];
break;
case MAP:
case LIST: {
// Since the offsets column in cudf is `size_type`,
// If the limit exceeds then value will be 0, which is Fail.
Expand Down Expand Up @@ -1796,7 +1800,7 @@ __global__ void __launch_bounds__(block_size)
}
}
// Aggregate num of elements for the chunk
if (s->chunk.type_kind == LIST) {
if (s->chunk.type_kind == LIST or s->chunk.type_kind == MAP) {
list_child_elements = block_reduce(temp_storage.blk_uint64).Sum(list_child_elements);
}
__syncthreads();
Expand All @@ -1813,14 +1817,16 @@ __global__ void __launch_bounds__(block_size)
__syncthreads();
if (t == 0) {
s->top.data.cur_row += s->top.data.nrows;
if (s->chunk.type_kind == LIST) { s->num_child_rows += list_child_elements; }
if (s->chunk.type_kind == LIST or s->chunk.type_kind == MAP) {
s->num_child_rows += list_child_elements;
}
if (s->is_string && !is_dictionary(s->chunk.encoding_kind) && s->top.data.max_vals > 0) {
s->chunk.dictionary_start += s->vals.u32[s->top.data.max_vals - 1];
}
}
__syncthreads();
}
if (t == 0 and s->chunk.type_kind == LIST) {
if (t == 0 and (s->chunk.type_kind == LIST or s->chunk.type_kind == MAP)) {
if (num_rowgroups > 0) {
row_groups[blockIdx.y][blockIdx.x].num_child_rows = s->num_child_rows;
}
Expand Down
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