group by optimization
This commit is contained in:
+3
-3
@@ -107,9 +107,9 @@ ULongT = Types(8, name = 'uint64', sqlname = 'UINT64', fp_type=DoubleT)
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UIntT = Types(7, name = 'uint32', sqlname = 'UINT32', long_type=ULongT, fp_type=FloatT)
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UShortT = Types(6, name = 'uint16', sqlname = 'UINT16', long_type=ULongT, fp_type=FloatT)
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UByteT = Types(5, name = 'uint8', sqlname = 'UINT8', long_type=ULongT, fp_type=FloatT)
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StrT = Types(200, name = 'str', cname = 'const char*', sqlname='TEXT', ctype_name = 'types::ASTR')
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TextT = Types(200, name = 'text', cname = 'const char*', sqlname='TEXT', ctype_name = 'types::ASTR')
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VarcharT = Types(200, name = 'varchar', cname = 'const char*', sqlname='VARCHAR', ctype_name = 'types::ASTR')
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StrT = Types(200, name = 'str', cname = 'string_view', sqlname='TEXT', ctype_name = 'types::ASTR')
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TextT = Types(200, name = 'text', cname = 'string_view', sqlname='TEXT', ctype_name = 'types::ASTR')
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VarcharT = Types(200, name = 'varchar', cname = 'string_view', sqlname='VARCHAR', ctype_name = 'types::ASTR')
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VoidT = Types(200, name = 'void', cname = 'void', sqlname='Null', ctype_name = 'types::None')
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class VectorT(Types):
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+1
-1
@@ -2,7 +2,7 @@ import struct
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import readline
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from typing import List
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name : str = input()
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name : str = input('Filename (in path ./procedures/<filename>.aqp):')
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def write():
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s : str = input()
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+73
-30
@@ -339,8 +339,8 @@ class projection(ast_node):
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return ', '.join([self.pyname2cname[n.name] for n in lst_names])
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else:
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return self.pyname2cname[proj_name]
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for key, val in proj_map.items():
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gb_tovec = [False] * len(proj_map)
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for i, (key, val) in enumerate(proj_map.items()):
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if type(val[1]) is str:
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x = True
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y = get_proj_name
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@@ -357,22 +357,27 @@ class projection(ast_node):
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out_typenames[key] = decltypestring
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else:
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out_typenames[key] = val[0].cname
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if (type(val[2].udf_called) is udf and # should bulkret also be colref?
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elemental_ret_udf = (
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type(val[2].udf_called) is udf and # should bulkret also be colref?
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val[2].udf_called.return_pattern == udf.ReturnPattern.elemental_return
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or
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self.group_node and
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(self.group_node.use_sp_gb and
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)
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folding_vector_groups = (
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self.group_node and
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(
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self.group_node.use_sp_gb and
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val[2].cols_mentioned.intersection(
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self.datasource.all_cols().difference(
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self.datasource.get_joint_cols(self.group_node.refs)
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))
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) and val[2].is_compound # compound val not in key
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# or
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# val[2].is_compound > 1
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# (not self.group_node and val[2].is_compound)
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):
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out_typenames[key] = f'vector_type<{out_typenames[key]}>'
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self.out_table.columns[key].compound = True
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)
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)
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) and
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val[2].is_compound # compound val not in key
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)
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if (elemental_ret_udf or folding_vector_groups):
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out_typenames[key] = f'vector_type<{out_typenames[key]}>'
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self.out_table.columns[key].compound = True
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if self.group_node is not None and self.group_node.use_sp_gb:
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gb_tovec[i] = True
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outtable_col_nameslist = ', '.join([f'"{c.name}"' for c in self.out_table.columns])
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self.outtable_col_names = 'names_' + base62uuid(4)
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self.context.emitc(f'const char* {self.outtable_col_names}[] = {{{outtable_col_nameslist}}};')
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@@ -384,12 +389,14 @@ class projection(ast_node):
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gb_vartable : Dict[str, Union[str, int]] = deepcopy(self.pyname2cname)
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gb_cexprs : List[str] = []
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gb_colnames : List[str] = []
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gb_types : List[Types] = []
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for key, val in proj_map.items():
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col_name = 'col_' + base62uuid(6)
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self.context.emitc(f'decltype(auto) {col_name} = {self.out_table.contextname_cpp}->get_col<{key}>();')
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gb_cexprs.append((col_name, val[2]))
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gb_colnames.append(col_name)
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self.group_node.finalize(gb_cexprs, gb_vartable, gb_colnames)
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gb_types.append(val[0])
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self.group_node.finalize(gb_cexprs, gb_vartable, gb_colnames, gb_types, gb_tovec)
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else:
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for i, (key, val) in enumerate(proj_map.items()):
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if type(val[1]) is int:
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@@ -533,6 +540,7 @@ class groupby_c(ast_node):
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def init(self, node : List[Tuple[expr, Set[ColRef]]]):
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self.proj : projection = self.parent
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self.glist : List[Tuple[expr, Set[ColRef]]] = node
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self.vecs : str = 'vecs_' + base62uuid(3)
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return super().init(node)
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def produce(self, node : List[Tuple[expr, Set[ColRef]]]):
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@@ -561,21 +569,22 @@ class groupby_c(ast_node):
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e = g_str
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g_contents_list.append(e)
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first_col = g_contents_list[0]
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self.total_sz = 'len_' + base62uuid(4)
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self.context.emitc(f'uint32_t {self.total_sz} = {first_col}.size;')
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g_contents_decltype = [f'decays<decltype({c})::value_t>' for c in g_contents_list]
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g_contents = ', '.join(
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[f'{c}[{scanner_itname}]' for c in g_contents_list]
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)
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self.context.emitc(f'typedef record<{",".join(g_contents_decltype)}> {self.group_type};')
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self.context.emitc(f'ankerl::unordered_dense::map<{self.group_type}, vector_type<uint32_t>, '
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f'transTypes<{self.group_type}, hasher>> {self.group};')
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self.context.emitc(f'{self.group}.reserve({first_col}.size);')
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self.context.emitc(f'AQHashTable<{self.group_type}, '
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f'transTypes<{self.group_type}, hasher>> {self.group} {{{self.total_sz}}};')
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self.n_grps = len(self.glist)
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self.scanner = scan(self, first_col + '.size', it_name=scanner_itname)
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self.scanner.add(f'{self.group}[forward_as_tuple({g_contents})].emplace_back({self.scanner.it_var});')
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self.scanner = scan(self, self.total_sz, it_name=scanner_itname)
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self.scanner.add(f'{self.group}.hashtable_push(forward_as_tuple({g_contents}), {self.scanner.it_var});')
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def consume(self, _):
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self.scanner.finalize()
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self.context.emitc(f'auto {self.vecs} = {self.group}.ht_postproc({self.total_sz});')
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# def deal_with_assumptions(self, assumption:assumption, out:TableInfo):
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# gscanner = scan(self, self.group)
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# val_var = 'val_'+base62uuid(7)
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@@ -583,16 +592,40 @@ class groupby_c(ast_node):
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# gscanner.add(f'{self.datasource.cxt_name}->order_by<{assumption.result()}>(&{val_var});')
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# gscanner.finalize()
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def finalize(self, cexprs : List[Tuple[str, expr]], var_table : Dict[str, Union[str, int]], col_names : List[str]):
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for c in col_names:
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def finalize(self, cexprs : List[Tuple[str, expr]], var_table : Dict[str, Union[str, int]],
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col_names : List[str], col_types : List[Types], col_tovec : List[bool]):
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tovec_columns = set()
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for i, c in enumerate(col_names):
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self.context.emitc(f'{c}.reserve({self.group}.size());')
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if col_tovec[i]: # and type(col_types[i]) is VectorT:
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typename : Types = col_types[i] # .inner_type
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self.context.emitc(f'auto buf_{c} = static_cast<{typename.cname} *>(malloc({self.total_sz} * sizeof({typename.cname})));')
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tovec_columns.add(c)
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self.arr_len = 'arrlen_' + base62uuid(3)
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self.arr_values = 'arrvals_' + base62uuid(3)
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gscanner = scan(self, self.group, loop_style = 'for_each')
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if len(tovec_columns):
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self.context.emitc(f'auto {self.arr_len} = {self.group}.size();')
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self.context.emitc(f'auto {self.arr_values} = {self.group}.values();')
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preproc_scanner = scan(self, self.arr_len)
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preproc_scanner_it = preproc_scanner.it_var
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for c in tovec_columns:
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preproc_scanner.add(f'{c}[{preproc_scanner_it}].init_from'
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f'({self.vecs}[{preproc_scanner_it}].size,'
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f' {"buf_" + c} + {self.group}.ht_base'
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f'[{preproc_scanner_it}]);'
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)
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preproc_scanner.finalize()
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# gscanner = scan(self, self.group, loop_style = 'for_each')
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gscanner = scan(self, self.arr_len)
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key_var = 'key_'+base62uuid(7)
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val_var = 'val_'+base62uuid(7)
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gscanner.add(f'auto &{key_var} = {gscanner.it_var}.first;', position = 'front')
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gscanner.add(f'auto &{val_var} = {gscanner.it_var}.second;', position = 'front')
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# gscanner.add(f'auto &{key_var} = {gscanner.it_var}.first;', position = 'front')
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# gscanner.add(f'auto &{val_var} = {gscanner.it_var}.second;', position = 'front')
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gscanner.add(f'auto &{key_var} = {self.arr_values}[{gscanner.it_var}];', position = 'front')
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gscanner.add(f'auto &{val_var} = {self.vecs}[{gscanner.it_var}];', position = 'front')
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len_var = None
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def define_len_var():
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nonlocal len_var
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@@ -627,7 +660,7 @@ class groupby_c(ast_node):
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materialize_builtin = materialize_builtin,
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count=lambda:f'{val_var}.size')
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for ce in cexprs:
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for i, ce in enumerate(cexprs):
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ex = ce[1]
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materialize_builtin = {}
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if type(ex.udf_called) is udf:
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@@ -640,7 +673,16 @@ class groupby_c(ast_node):
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materialize_builtin['_builtin_ret'] = f'{ce[0]}.back()'
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gscanner.add(f'{ex.eval(c_code = True, y=get_var_names, materialize_builtin = materialize_builtin)};\n')
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continue
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gscanner.add(f'{ce[0]}.emplace_back({get_var_names_ex(ex)});\n')
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if col_tovec[i]:
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if ex.opname == 'avgs':
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patch_expr = get_var_names_ex(ex)
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patch_expr = patch_expr[:patch_expr.rindex(')')]
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patch_expr += ', ' + f'{ce[0]}[{gscanner.it_var}]' + ')'
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gscanner.add(f'{patch_expr};\n')
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else:
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gscanner.add(f'{ce[0]}[{gscanner.it_var}] = {get_var_names_ex(ex)};\n')
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else:
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gscanner.add(f'{ce[0]}.emplace_back({get_var_names_ex(ex)});\n')
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gscanner.finalize()
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@@ -718,10 +760,11 @@ class groupby(ast_node):
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# self.parent.var_table.
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self.parent.col_ext.update(l[1])
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def finalize(self, cexprs : List[Tuple[str, expr]], var_table : Dict[str, Union[str, int]], col_names : List[str]):
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def finalize(self, cexprs : List[Tuple[str, expr]], var_table : Dict[str, Union[str, int]],
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col_names : List[str], col_types : List[Types], col_tovec : List[bool]):
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if self.use_sp_gb:
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self.dedicated_gb = groupby_c(self.parent, self.dedicated_glist)
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self.dedicated_gb.finalize(cexprs, var_table, col_names)
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self.dedicated_gb.finalize(cexprs, var_table, col_names, col_types, col_tovec)
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class join(ast_node):
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@@ -132,7 +132,3 @@ namespace ankerl::unordered_dense{
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struct hash<std::tuple<Types...>> : public hasher<Types...>{ };
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}
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struct aq_hashtable_value_t {
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uint32_t id;
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uint32_t cnt;
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};
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@@ -295,6 +295,7 @@ void initialize_module(const char* module_name, void* module_handle, Context* cx
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printf("Warning: module %s have no session support.\n", module_name);
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}
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}
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#pragma endregion
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int dll_main(int argc, char** argv, Context* cxt){
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aq_timer timer;
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+28
-28
@@ -1062,7 +1062,7 @@ public:
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// template <class K>
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// bool hashtable_push(K&& key) {
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// auto it_isinserted = try_emplace(std::forward<K>(key), 1);
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// if (!it_isinserted.second)
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// if (!it_isinserted.second)
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// ++ it_isinserted.first->second;
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// return it_isinserted.second;
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// }
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@@ -1113,8 +1113,8 @@ public:
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template <class K,
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typename Q = T,
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typename H = Hash,
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typename KE = KeyEqual,
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std::enable_if_t<!is_map_v<Q> && is_transparent_v<H, KE>, bool> = true>
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typename KE = KeyEqual>//,
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//std::enable_if_t<!is_map_v<Q> && is_transparent_v<H, KE>, bool> = true>
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auto hashtable_push(K&& key) -> unsigned {
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if (is_full()) {
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increase_size();
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@@ -1141,35 +1141,35 @@ template <class K,
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place_and_shift_up({dist_and_fingerprint, value_idx}, bucket_idx);
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return static_cast<uint32_t>(value_idx);
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}
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template <class... Args>
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auto hashtable_push(Args&&... args) -> unsigned {
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if (is_full()) {
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increase_size();
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}
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// template <class... Args>
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// auto hashtable_push(Args&&... args) -> unsigned {
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// if (is_full()) {
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// increase_size();
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// }
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// we have to instantiate the value_type to be able to access the key.
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// 1. emplace_back the object so it is constructed. 2. If the key is already there, pop it later in the loop.
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auto& key = get_key(m_values.emplace_back(std::forward<Args>(args)...));
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auto hash = mixed_hash(key);
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auto dist_and_fingerprint = dist_and_fingerprint_from_hash(hash);
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auto bucket_idx = bucket_idx_from_hash(hash);
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// // we have to instantiate the value_type to be able to access the key.
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// // 1. emplace_back the object so it is constructed. 2. If the key is already there, pop it later in the loop.
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// auto& key = get_key(m_values.emplace_back(std::forward<Args>(args)...));
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// auto hash = mixed_hash(key);
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// auto dist_and_fingerprint = dist_and_fingerprint_from_hash(hash);
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// auto bucket_idx = bucket_idx_from_hash(hash);
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while (dist_and_fingerprint <= at(m_buckets, bucket_idx).m_dist_and_fingerprint) {
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if (dist_and_fingerprint == at(m_buckets, bucket_idx).m_dist_and_fingerprint &&
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m_equal(key, get_key(m_values[at(m_buckets, bucket_idx).m_value_idx]))) {
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m_values.pop_back(); // value was already there, so get rid of it
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return static_cast<uint32_t>(at(m_buckets, bucket_idx).m_value_idx);
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}
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dist_and_fingerprint = dist_inc(dist_and_fingerprint);
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bucket_idx = next(bucket_idx);
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}
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// while (dist_and_fingerprint <= at(m_buckets, bucket_idx).m_dist_and_fingerprint) {
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// if (dist_and_fingerprint == at(m_buckets, bucket_idx).m_dist_and_fingerprint &&
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// m_equal(key, get_key(m_values[at(m_buckets, bucket_idx).m_value_idx]))) {
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// m_values.pop_back(); // value was already there, so get rid of it
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// return static_cast<uint32_t>(at(m_buckets, bucket_idx).m_value_idx);
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// }
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// dist_and_fingerprint = dist_inc(dist_and_fingerprint);
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// bucket_idx = next(bucket_idx);
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// }
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// value is new, place the bucket and shift up until we find an empty spot
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auto value_idx = static_cast<value_idx_type>(m_values.size() - 1);
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place_and_shift_up({dist_and_fingerprint, value_idx}, bucket_idx);
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// // value is new, place the bucket and shift up until we find an empty spot
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// auto value_idx = static_cast<value_idx_type>(m_values.size() - 1);
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// place_and_shift_up({dist_and_fingerprint, value_idx}, bucket_idx);
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return static_cast<uint32_t>(value_idx);
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}
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// return static_cast<uint32_t>(value_idx);
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// }
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template <class... Args>
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auto emplace(Args&&... args) -> std::pair<iterator, bool> {
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if (is_full()) {
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@@ -427,6 +427,19 @@ constexpr vector_type<std::string_view>::vector_type(const uint32_t size, void*
|
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// }
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||||
// }
|
||||
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// template<template <typename> class VT>
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// inline void
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// prealloc_vector (VT &vt, uint32_t sz) {
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// vt.reserve(sz);
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// }
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|
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// template<class T>
|
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// inline void
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// prealloc_vector (vector_type<vector_type<T>> &vt,
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// uint32_t outer_sz, uint32_t inner_sz) {
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// vt.reserve(outer_sz);
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// auto mem = static_cast<T*>(malloc(inner_sz * sizeof(T)));
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||||
// }
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||||
template <>
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class vector_type<void> {
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||||
@@ -460,4 +473,48 @@ public:
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vector_type<void> subvec_deep(uint32_t);
|
||||
};
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||||
#pragma pack(pop)
|
||||
|
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template <class Key, class Hash>
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class AQHashTable : public ankerl::unordered_dense::set<Key, Hash> {
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||||
public:
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uint32_t* reversemap, *mapbase, *ht_base;
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AQHashTable() = default;
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||||
explicit AQHashTable(uint32_t sz)
|
||||
: ankerl::unordered_dense::set<Key, Hash>{} {
|
||||
this->reserve(sz);
|
||||
reversemap = static_cast<uint32_t *>(malloc(sizeof(uint32_t) * sz * 2));
|
||||
mapbase = reversemap + sz;
|
||||
ht_base = static_cast<uint32_t *>(calloc(sz, sizeof(uint32_t)));
|
||||
}
|
||||
|
||||
void init(uint32_t sz) {
|
||||
ankerl::unordered_dense::set<Key, Hash>::reserve(sz);
|
||||
reversemap = static_cast<uint32_t *>(malloc(sizeof(uint32_t) * sz * 2));
|
||||
mapbase = reversemap + sz;
|
||||
ht_base = static_cast<uint32_t *>(calloc(sz, sizeof(uint32_t)));
|
||||
}
|
||||
|
||||
inline void hashtable_push(Key&& k, uint32_t i){
|
||||
reversemap[i] = ankerl::unordered_dense::set<Key, Hash>::hashtable_push(std::forward<Key&&>(k));
|
||||
++ht_base[reversemap[i]];
|
||||
}
|
||||
|
||||
auto ht_postproc(uint32_t sz) {
|
||||
auto& arr_values = this->values();
|
||||
const auto& len = this->size();
|
||||
|
||||
auto vecs = static_cast<vector_type<uint32_t>*>(malloc(sizeof(vector_type<uint32_t>) * len));
|
||||
vecs[0].init_from(ht_base[0], mapbase);
|
||||
for (uint32_t i = 1; i < len; ++i) {
|
||||
vecs[i].init_from(ht_base[i], mapbase + ht_base[i - 1]);
|
||||
ht_base[i] += ht_base[i - 1];
|
||||
}
|
||||
for (uint32_t i = 0; i < sz; ++i) {
|
||||
auto id = reversemap[i];
|
||||
mapbase[--ht_base[id]] = i;
|
||||
}
|
||||
return vecs;
|
||||
}
|
||||
};
|
||||
|
||||
#endif
|
||||
|
||||
Reference in New Issue
Block a user