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This commit is contained in:
bill
2023-01-09 22:59:41 +08:00
parent 181abacc55
commit aee803adce
7 changed files with 163 additions and 66 deletions
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reconstruct/ast.py
+73 -30
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@@ -339,8 +339,8 @@ class projection(ast_node):
return ', '.join([self.pyname2cname[n.name] for n in lst_names])
else:
return self.pyname2cname[proj_name]
for key, val in proj_map.items():
gb_tovec = [False] * len(proj_map)
for i, (key, val) in enumerate(proj_map.items()):
if type(val[1]) is str:
x = True
y = get_proj_name
@@ -357,22 +357,27 @@ class projection(ast_node):
out_typenames[key] = decltypestring
else:
out_typenames[key] = val[0].cname
if (type(val[2].udf_called) is udf and # should bulkret also be colref?
elemental_ret_udf = (
type(val[2].udf_called) is udf and # should bulkret also be colref?
val[2].udf_called.return_pattern == udf.ReturnPattern.elemental_return
or
self.group_node and
(self.group_node.use_sp_gb and
)
folding_vector_groups = (
self.group_node and
(
self.group_node.use_sp_gb and
val[2].cols_mentioned.intersection(
self.datasource.all_cols().difference(
self.datasource.get_joint_cols(self.group_node.refs)
))
) and val[2].is_compound # compound val not in key
# or
# val[2].is_compound > 1
# (not self.group_node and val[2].is_compound)
):
out_typenames[key] = f'vector_type<{out_typenames[key]}>'
self.out_table.columns[key].compound = True
)
)
) and
val[2].is_compound # compound val not in key
)
if (elemental_ret_udf or folding_vector_groups):
out_typenames[key] = f'vector_type<{out_typenames[key]}>'
self.out_table.columns[key].compound = True
if self.group_node is not None and self.group_node.use_sp_gb:
gb_tovec[i] = True
outtable_col_nameslist = ', '.join([f'"{c.name}"' for c in self.out_table.columns])
self.outtable_col_names = 'names_' + base62uuid(4)
self.context.emitc(f'const char* {self.outtable_col_names}[] = {{{outtable_col_nameslist}}};')
@@ -384,12 +389,14 @@ class projection(ast_node):
gb_vartable : Dict[str, Union[str, int]] = deepcopy(self.pyname2cname)
gb_cexprs : List[str] = []
gb_colnames : List[str] = []
gb_types : List[Types] = []
for key, val in proj_map.items():
col_name = 'col_' + base62uuid(6)
self.context.emitc(f'decltype(auto) {col_name} = {self.out_table.contextname_cpp}->get_col<{key}>();')
gb_cexprs.append((col_name, val[2]))
gb_colnames.append(col_name)
self.group_node.finalize(gb_cexprs, gb_vartable, gb_colnames)
gb_types.append(val[0])
self.group_node.finalize(gb_cexprs, gb_vartable, gb_colnames, gb_types, gb_tovec)
else:
for i, (key, val) in enumerate(proj_map.items()):
if type(val[1]) is int:
@@ -533,6 +540,7 @@ class groupby_c(ast_node):
def init(self, node : List[Tuple[expr, Set[ColRef]]]):
self.proj : projection = self.parent
self.glist : List[Tuple[expr, Set[ColRef]]] = node
self.vecs : str = 'vecs_' + base62uuid(3)
return super().init(node)
def produce(self, node : List[Tuple[expr, Set[ColRef]]]):
@@ -561,21 +569,22 @@ class groupby_c(ast_node):
e = g_str
g_contents_list.append(e)
first_col = g_contents_list[0]
self.total_sz = 'len_' + base62uuid(4)
self.context.emitc(f'uint32_t {self.total_sz} = {first_col}.size;')
g_contents_decltype = [f'decays<decltype({c})::value_t>' for c in g_contents_list]
g_contents = ', '.join(
[f'{c}[{scanner_itname}]' for c in g_contents_list]
)
self.context.emitc(f'typedef record<{",".join(g_contents_decltype)}> {self.group_type};')
self.context.emitc(f'ankerl::unordered_dense::map<{self.group_type}, vector_type<uint32_t>, '
f'transTypes<{self.group_type}, hasher>> {self.group};')
self.context.emitc(f'{self.group}.reserve({first_col}.size);')
self.context.emitc(f'AQHashTable<{self.group_type}, '
f'transTypes<{self.group_type}, hasher>> {self.group} {{{self.total_sz}}};')
self.n_grps = len(self.glist)
self.scanner = scan(self, first_col + '.size', it_name=scanner_itname)
self.scanner.add(f'{self.group}[forward_as_tuple({g_contents})].emplace_back({self.scanner.it_var});')
self.scanner = scan(self, self.total_sz, it_name=scanner_itname)
self.scanner.add(f'{self.group}.hashtable_push(forward_as_tuple({g_contents}), {self.scanner.it_var});')
def consume(self, _):
self.scanner.finalize()
self.context.emitc(f'auto {self.vecs} = {self.group}.ht_postproc({self.total_sz});')
# def deal_with_assumptions(self, assumption:assumption, out:TableInfo):
# gscanner = scan(self, self.group)
# val_var = 'val_'+base62uuid(7)
@@ -583,16 +592,40 @@ class groupby_c(ast_node):
# gscanner.add(f'{self.datasource.cxt_name}->order_by<{assumption.result()}>(&{val_var});')
# gscanner.finalize()
def finalize(self, cexprs : List[Tuple[str, expr]], var_table : Dict[str, Union[str, int]], col_names : List[str]):
for c in col_names:
def finalize(self, cexprs : List[Tuple[str, expr]], var_table : Dict[str, Union[str, int]],
col_names : List[str], col_types : List[Types], col_tovec : List[bool]):
tovec_columns = set()
for i, c in enumerate(col_names):
self.context.emitc(f'{c}.reserve({self.group}.size());')
if col_tovec[i]: # and type(col_types[i]) is VectorT:
typename : Types = col_types[i] # .inner_type
self.context.emitc(f'auto buf_{c} = static_cast<{typename.cname} *>(malloc({self.total_sz} * sizeof({typename.cname})));')
tovec_columns.add(c)
self.arr_len = 'arrlen_' + base62uuid(3)
self.arr_values = 'arrvals_' + base62uuid(3)
gscanner = scan(self, self.group, loop_style = 'for_each')
if len(tovec_columns):
self.context.emitc(f'auto {self.arr_len} = {self.group}.size();')
self.context.emitc(f'auto {self.arr_values} = {self.group}.values();')
preproc_scanner = scan(self, self.arr_len)
preproc_scanner_it = preproc_scanner.it_var
for c in tovec_columns:
preproc_scanner.add(f'{c}[{preproc_scanner_it}].init_from'
f'({self.vecs}[{preproc_scanner_it}].size,'
f' {"buf_" + c} + {self.group}.ht_base'
f'[{preproc_scanner_it}]);'
)
preproc_scanner.finalize()
# gscanner = scan(self, self.group, loop_style = 'for_each')
gscanner = scan(self, self.arr_len)
key_var = 'key_'+base62uuid(7)
val_var = 'val_'+base62uuid(7)
gscanner.add(f'auto &{key_var} = {gscanner.it_var}.first;', position = 'front')
gscanner.add(f'auto &{val_var} = {gscanner.it_var}.second;', position = 'front')
# gscanner.add(f'auto &{key_var} = {gscanner.it_var}.first;', position = 'front')
# gscanner.add(f'auto &{val_var} = {gscanner.it_var}.second;', position = 'front')
gscanner.add(f'auto &{key_var} = {self.arr_values}[{gscanner.it_var}];', position = 'front')
gscanner.add(f'auto &{val_var} = {self.vecs}[{gscanner.it_var}];', position = 'front')
len_var = None
def define_len_var():
nonlocal len_var
@@ -627,7 +660,7 @@ class groupby_c(ast_node):
materialize_builtin = materialize_builtin,
count=lambda:f'{val_var}.size')
for ce in cexprs:
for i, ce in enumerate(cexprs):
ex = ce[1]
materialize_builtin = {}
if type(ex.udf_called) is udf:
@@ -640,7 +673,16 @@ class groupby_c(ast_node):
materialize_builtin['_builtin_ret'] = f'{ce[0]}.back()'
gscanner.add(f'{ex.eval(c_code = True, y=get_var_names, materialize_builtin = materialize_builtin)};\n')
continue
gscanner.add(f'{ce[0]}.emplace_back({get_var_names_ex(ex)});\n')
if col_tovec[i]:
if ex.opname == 'avgs':
patch_expr = get_var_names_ex(ex)
patch_expr = patch_expr[:patch_expr.rindex(')')]
patch_expr += ', ' + f'{ce[0]}[{gscanner.it_var}]' + ')'
gscanner.add(f'{patch_expr};\n')
else:
gscanner.add(f'{ce[0]}[{gscanner.it_var}] = {get_var_names_ex(ex)};\n')
else:
gscanner.add(f'{ce[0]}.emplace_back({get_var_names_ex(ex)});\n')
gscanner.finalize()
@@ -718,10 +760,11 @@ class groupby(ast_node):
# self.parent.var_table.
self.parent.col_ext.update(l[1])
def finalize(self, cexprs : List[Tuple[str, expr]], var_table : Dict[str, Union[str, int]], col_names : List[str]):
def finalize(self, cexprs : List[Tuple[str, expr]], var_table : Dict[str, Union[str, int]],
col_names : List[str], col_types : List[Types], col_tovec : List[bool]):
if self.use_sp_gb:
self.dedicated_gb = groupby_c(self.parent, self.dedicated_glist)
self.dedicated_gb.finalize(cexprs, var_table, col_names)
self.dedicated_gb.finalize(cexprs, var_table, col_names, col_types, col_tovec)
class join(ast_node):