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from pprint import pprint
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from tqdm import tqdm
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import functools
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import dolphindb as ddb
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from DDBLoader import DDBLoader
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def load_ddb_table(hft_tbl_name):
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def decorator(func):
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@functools.wraps(func)
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def wrapper(self, *args, **kwargs):
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self.ddb_sess.run("""
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// 载入计算使用的原始数据：分钟线数据
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tbl = loadTable("{hft_ddb_path}", "{hft_tbl_name}");
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""".format(
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hft_ddb_path = DDBLoader.ddb_path,
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hft_tbl_name = hft_tbl_name,
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))
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print('Did load', hft_tbl_name)
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return func(self)
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return wrapper
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return decorator
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class DailyFactor(object):
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#ddb_hft_path = "dfs://hft_stock_ts"
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#ddb_hft_dbname = "db_hft_stock"
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ddb_daily_path = "dfs://daily_stock_ts"
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ddb_daily_dbname = "db_daily_stock"
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ddb_config = {
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'host' : '192.168.1.167',
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'username' : 'admin',
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'password' : '123456',
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}
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# 这里的partition数量未必需要和hft表的一致
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# 当读取hft表的时候，需要使用DDBLoader中的`num_code_partition`，而不是此字段
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num_code_partition = 50
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def __init__(self):
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self.ddb_sess = ddb.session(self.ddb_config['host'], 8848)
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self.ddb_sess.login(self.ddb_config['username'], self.ddb_config['password'])
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def create_ddb_database(self):
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"""
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因为日频数据量较小，内部可以使用m_nDate作为sort_key，所以分区仅需要对stock_id做[HASH, 50]即可，因此不需要输入calendar数据
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"""
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self.ddb_sess.run("""
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daily_stock_ts = database(
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"{ddb_hft_path}",
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HASH, [SYMBOL, {num_code_parition}],
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engine = 'TSDB'
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)
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""".format(
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ddb_hft_path = DDBLoader.ddb_path,
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num_code_partition = self.num_code_partition
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))
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print('Did create database')
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def load_ddb_database(self):
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self.ddb_sess.run("""
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{dbName} = database(
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directory = '{dbPath}',
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partitionType = HASH,
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partitionScheme = [SYMBOL, {num_code_partition}],
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engine = 'TSDB'
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)
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""".format(
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dbName = self.ddb_daily_dbname,
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dbPath = self.ddb_daily_path,
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num_code_partition = self.num_code_partition
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))
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print('Did load database.')
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def append_factor_columns(self, factor_name_list, memory_tbl_name, partition_tbl_name):
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code = """
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addColumn({partition_tbl_name}, {col_name_list}, {col_type_list});
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""".format(
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partition_tbl_name = partition_tbl_name,
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col_name_list = '`' + '`'.join(factor_name_list),
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col_type_list = '[' + ','.join(['DOUBLE']*len(factor_name_list)) + ']'
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)
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print('Will add columns via script:')
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print(code)
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self.ddb_sess.run(code)
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code = """
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{partition_tbl_name}.tableInsert({memory_tbl_name})
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""".format(
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partition_tbl_name = partition_tbl_name,
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memory_tbl_name = memory_tbl_name
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)
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print('Will append date via script:')
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print(code)
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self.ddb_sess.run(code)
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def append_to_partition_table(self, partition_tbl_name, memory_tbl_name):
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self.ddb_sess.run("""
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{partition_tbl_name}.tableInsert({memory_tbl_name})
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""".format(
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partition_tbl_name = partition_tbl_name,
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memory_tbl_name = memory_tbl_name
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))
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def create_factor_partition_table(self, partition_tbl_name, memory_tbl_name):
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"""
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把数据从内存表（`memory_tbl_name`）添加到分区表（`partition_tbl_name`）
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"""
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# createPartitionedTable(
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# dbHandle, table, tableName,
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# [partitionColumns], [compressMethods],
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# [sortColumns], [keepDuplicates=ALL], [sortKeyMappingFunction])
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code = """
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// 保证创建新的分区表不会和已经存在表冲突
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if (existsTable("{ddb_daily_path}", "{partition_tbl_name}")) {{
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dropTable({ddb_daily_dbname}, "{partition_tbl_name}");
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}}
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{partition_tbl_name} = createPartitionedTable(
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dbHandle = {ddb_daily_dbname},
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table = {memory_tbl_name},
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tableName = "{partition_tbl_name}",
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partitionColumns = 'code',
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compressMethods = {{'m_nDate' : 'delta'}},
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sortColumns = `code`m_nDate
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);
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""".format(
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ddb_daily_path = self.ddb_daily_path,
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ddb_daily_dbname = self.ddb_daily_dbname,
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partition_tbl_name = partition_tbl_name,
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memory_tbl_name = memory_tbl_name,
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)
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print('Will create partitioned factor table via script:')
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print(code)
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self.ddb_sess.run(code)
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@load_ddb_table("KLinePartitioned")
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def make_kurto_memory_table(self):
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memory_table_name = "kurto"
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code_tpl = """
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// 需要首先创建分钟线收益表
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// 使用`context by`使得计算结果仍然为一个序列
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// 使用`where partition()`来逐个加载分区
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ret_sql = select
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code, m_nDate, eachPre(\, m_nClose)-1.0 as ret
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from tbl
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where partition(code, {partition_id})
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context by m_nDate;
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// 计算kurto指标，`ret`表中每日第一条记录为空，似乎并不造成影响
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kurto_sql = select
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code, m_nDate, sqrt(239) * sum(pow(ret, 3)) / pow(sum(pow(ret, 2)), 1.5) as kurto
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from ret_sql
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group by code, m_nDate;
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"""
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with tqdm(range(DDBLoader.num_code_partition)) as pbar:
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#with tqdm(range(1)) as pbar:
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for partition_id in pbar:
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self.ddb_sess.run(code_tpl.format(
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partition_id = partition_id,
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))
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# 因为原表有50个分区，需要逐个计算，因此先创建一个内存临时表
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# 否则一旦第一个分区插入分区表后，就无法再插入后续只包含部分字段的数据了
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if partition_id == 0:
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self.ddb_sess.run("""
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{memory_table_name} = table(kurto_sql)
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""".format(
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memory_table_name = memory_table_name
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))
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# 上面`table`语句仅仅是创建表结构，
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# 然后使用`tableInsert`把真实数据插入进去
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self.ddb_sess.run("""
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{memory_table_name}.tableInsert(kurto_sql)
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""".format(
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memory_table_name = memory_table_name
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))
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print('Did finish all parititons for kurto.')
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pprint(self.ddb_sess.run(f"{memory_table_name}"))
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return memory_table_name
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def main():
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factor = DailyFactor()
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factor.load_ddb_database()
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memory_table_name = factor.make_kurto_memory_table()
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factor.create_factor_partition_table(
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'hft_daily_factor',
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memory_table_name
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)
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factor.append_to_partition_table(
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'hft_daily_factor',
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memory_table_name
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)
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if __name__ == '__main__':
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main()
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