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hello_parquet.py
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""":mod:`hello_parquet` module to test all fields of a `pyarrow` table to db2
"""
#import pyarrow.parquet as pq
import pyarrow as pa
import pandas as pd
import pyarrow.parquet as pq
import os
import json
from datetime import datetime, time, timedelta, date
import pprint
import sys
import errno
from texttable import Texttable
import logging
import logging.handlers
from dateutil.relativedelta import relativedelta
import ibm_db
import ibm_db_dbi
import collections
import numpy as np
import decimal
import humanfriendly
import threading
import spclient_python
import time as time_mod
try:
os.mkdir('log')
except OSError as e:
if e.errno != errno.EEXIST:
print ("creating directory 'log' OSError %s" % e)
try:
os.remove(os.path.join("log", "hello_parquet.log"))
except OSError:
pass
import datetime as dt
class MyFormatter(logging.Formatter):
converter = dt.datetime.fromtimestamp
def formatTime(self, record, datefmt=None):
ct = self.converter(record.created)
if datefmt:
s = ct.strftime(datefmt)
else:
t = ct.strftime("%Y-%m-%d %H:%M:%S")
s = "%s,%03d" % (t, record.msecs)
return s
#format_hdlr = "%(asctime)s %(levelname)6s:%(lineno)4s - %(funcName)10s() %(message)s "
console_hdlr = logging.StreamHandler()
console_hdlr.setLevel(logging.INFO)
formatter = MyFormatter(fmt='%(asctime)s %(levelname)6s:%(lineno)4s - %(funcName)10s() %(message)s',
datefmt='%Y-%m-%d,%H:%M:%S.%f')
hdlr = logging.handlers.RotatingFileHandler(
os.path.join("log", "hello_parquet.log"),
maxBytes=10000000,
backupCount=3)
hdlr.setLevel(logging.INFO)
console_hdlr.setFormatter(formatter)
hdlr.setFormatter(formatter)
mylog = logging.getLogger(__name__)
mylog.setLevel(logging.INFO)
#log.addHandler(file_hdlr)
mylog.addHandler(console_hdlr)
mylog.addHandler(hdlr)
if sys.version_info > (3,):
import configparser # @UnusedImport
else:
import ConfigParser as configparser # @ImportRedefinition
config = None
DSN = None
def my_func():
return ""
def get_my_dict():
items = config.items(DSN)
my_dict = {}
for item in items:
key, value = item
my_dict[key.upper()] = value
return my_dict
def get_config(key, default):
global config, DSN
if config is None:
if sys.version_info > (3,):
config = configparser.ConfigParser()
else:
config = configparser.RawConfigParser()
try:
config.read("hello_parquet.ini")
DSN = config.get('DSN', 'DSN')
mylog.info("DSN='%s' cwd=%s" % (DSN, os.getcwd()))
except configparser.ParsingError as e:
mylog.error("ParsingError %s" % e)
sys.exit(0)
try:
local = config.get(DSN, key)
except configparser.Error as e:
local = default
cwd = os.getcwd()
mylog.error("""
type %s
error '%s'
using default %s='%s'
cwd %s
""" % (type(e), e, key, default, cwd))
return local
def merge_dicts(*dict_args):
"""
Given any number of dicts, shallow copy and merge into a new dict,
precedence goes to key value pairs in latter dicts.
"""
result = collections.defaultdict(my_func, {})
for dictionary in dict_args:
result.update(dictionary)
return result
def read_ini():
"""
This function set the DSN parameters, DB2_USER, DB2_PASSWORD, DB2_DATABASE
DB2_DATABASE is really the DSN on the db2cli.ini file, so is not the DB NAME
Returns
-------
:class:`collections.defaultdict`
"""
if os.path.exists("hello_parquet.ini"):
mylog.info("hello_parquet.ini present")
DB2_USER = get_config('DB2_USER', 'some_db2_user')
DB2_PASSWORD = get_config('DB2_PASSWORD', 'some_db2_password')
DB2_DATABASE = get_config('DB2_DATABASE', 'SAMPLE')
DB2_ALIAS = get_config('DB2_ALIAS', 'SAMPLE')
DB2_HOSTADDR = get_config('DB2_HOSTADDR', '*LOCAL')
DB2_INSTANCE = get_config('DB2_INSTANCE', 'DB2')
DB2_PORT = get_config('DB2_PORT', '50000')
DB2_PROTOCOL = get_config('DB2_PROTOCOL', 'IPC')
TEST_SIZE = get_config('TEST_SIZE', '100000')
DB2_ICHUNKSIZE = get_config('DB2_ICHUNKSIZE', '20000')
DB2_IDATABUFFERSIZE = get_config('DB2_IDATABUFFERSIZE', '0')
DB2_TABLESPACE = get_config('DB2_TABLESPACE', '')
DB2_COLUMN_ORIENTED = get_config('DB2_COLUMN_ORIENTED', '1')
DB2_DROPTABLE = get_config('DB2_DROPTABLE', '1')
DB2_MAXROWS = get_config('DB2_MAXROWS', '0')
all_keys = get_my_dict()
else:
mylog.error("hello_parquet.ini not present")
sys.exit(0)
my_dict = collections.defaultdict(my_func, {
'DB2_USER' : DB2_USER,
'DB2_PASSWORD' : DB2_PASSWORD,
'DB2_INSTANCE' : DB2_INSTANCE,
'DB2_HOSTADDR' : DB2_HOSTADDR,
'DB2_DATABASE' : DB2_DATABASE,
'DB2_PROTOCOL' : DB2_PROTOCOL,
'DB2_ALIAS' : DB2_ALIAS,
'DB2_PORT' : DB2_PORT,
'DB2_IDATABUFFERSIZE' : DB2_IDATABUFFERSIZE,
'DB2_ICHUNKSIZE' : DB2_ICHUNKSIZE,
'DB2_TABLESPACE' : DB2_TABLESPACE,
'DB2_COLUMN_ORIENTED' : DB2_COLUMN_ORIENTED,
'DB2_DROPTABLE' : DB2_DROPTABLE,
'DB2_MAXROWS' : DB2_MAXROWS,
'TEST_SIZE' : TEST_SIZE})
my_dict = merge_dicts(my_dict, all_keys)
return my_dict
def create_df():
"""Create pandas.DataFrame with dummy data and different field types
"""
v1 = datetime.today()
v2 = v1 - timedelta(days=5)
v3 = v1 - timedelta(days=6)
v4 = v1 - timedelta(days=7)
d1 = date.today()
d2 = d1 - timedelta(days=900)
d3 = date(1981, 10, 10)
d4 = date(1985, 10, 10)
t1 = datetime.today().time()
v2_for_time = v1 - timedelta(hours=3)
t2 = v2_for_time.time()
t3 = time(10, 10, 10, 4300)
rng = pd.date_range(date.today(), periods=4, freq='H')
dates = pd.Series([v1, v2, v3, v4])
mylog.info("dates \n%s" % dates)
mylog.info("dates.dt.date \n%s" % dates.dt.date)
mylog.info("dates.dt.date.dtype \n%s" % dates.dt.date.dtype)
df = pd.DataFrame({'c_float64' : [-1, 1.0, 2.5, 3.0],
'c_float32' : [-1, 1.0, 2.5, 3.0],
'c_string' : ['foo', 'bar', 'baz', 'lola'],
'c_boolean' : [True, False, True, False],
'c_datetime' : [v1, v2, v3, v4],
'c_time' : [t1, t2, t3, t3],
'c_timestamp_1h_frec' : rng,
'c_date' : [d1, d2, d3, d4]
},
index=list('abcd'))
df['c_timestamp_1h_frec'] = pd.to_datetime(df['c_timestamp_1h_frec'], unit='D')
df['c_date'] = df['c_date'].values.astype('datetime64[D]')
df['c_float32'] = df['c_float32'].values.astype('float32')
return df
def monitor_load(tablename):
return
data_read_ini = read_ini()
_db2_user = data_read_ini['DB2_USER']
conn = connect_to_db2(data_read_ini)
ret = ibm_db.exec_immediate(conn, "SET CURRENT SCHEMA CURRENT_USER")
ibm_db.free_result(ret)
for _i in range (6):
mylog.info("here '%s'" % tablename)
time_mod.sleep(2)
#spclient_python.python_monitor_load('%s' % (tablename))
def create_dummy_data_all_fields(size):
"""Create dummy data pyarrow table with all the different arrow::type fields
"""
column_names = ["c_uint8", "c_int8", "c_uint16", "c_int16",
"c_uint32", "c_int32", "c_uint64", "c_int64",
"c_float16",
"c_float32", "c_float64", "c_bool", "c_date32",
"c_date64_ms", "c_time64_us", "c_time64_ns", "c_time32_ms",
"c_time32_s", "c_timestamp_s", "c_timestamp_ms",
"c_timestamp_us",
"c_timestamp_ns",
"c_timestamp_ns_tz1",
"c_timestamp_us_tz1",
"c_timestamp_us_tz2",
"c_string_small",
"c_string_big",
"c_string_huge",
"c_binary",
"c_binary_big",
"c_binary_huge",
"c_fixed_size_binary_small",
"c_fixed_size_binary_big",
"c_fixed_size_binary_huge",
"c_decimal128"]
arrays = []
t4_ms = time(10, 10, 10, 999999)
t4_s = time(10, 10, 10, 0)
ctx = decimal.Context(prec=31, Emax=99999)
mylog.info("array of dummy data size '%s'" % "{:,}".format(size))
now = datetime.now()
dec1 = ctx.create_decimal("1.00000010000")
dec2 = ctx.create_decimal("1234.5678901234567890123456789")
np_decimal_list = np.empty(size, dtype=np.dtype('object'))
np_string_list = np.empty(size, dtype=np.dtype('object'))
np_string_list_big = np.empty(size, dtype=np.dtype('object'))
np_string_list_huge = np.empty(size, dtype=np.dtype('object'))
np_time64_list = np.empty(size, dtype=np.dtype('object'))
np_time64_ns_list = np.empty(size, dtype=np.dtype('object'))
step = 2
start_log = 70000
for i in range(size):
t3 = time(10, 10, 10, i % 999999)
t_nas = time(10, 10, 10, i % 999999)
np_time64_list[i] = t3
np_time64_ns_list[i] = t_nas
for i in range(size):
if i % 2 == 1:
np_decimal_list[i] = dec1
else:
np_decimal_list[i] = dec2
big = "juana" * 800
huge = "juana" * 20000
big_p = "petra" * 800
huge_p = "petra" * 20000
for i in range(size):
if i % 2 == 0:
np_string_list[i] = "juana"
np_string_list_big[i] = big
np_string_list_huge[i] = huge
else:
np_string_list[i] = "petra"
np_string_list_big[i] = big_p
np_string_list_huge[i] = huge_p
mylog.info("adding the rest of dummy data")
t1 = pa.int32()
t2 = pa.string()
t3 = pa.binary()
t4 = pa.binary(10)
t5 = pa.timestamp('ms')
t6 = pa.list_(t1)
mylog.debug("t6 '%s'" % t6)
_fields = [
pa.field('s0', t1),
pa.field('s1', t2),
pa.field('s2', t3),
pa.field('s4', t4)]
#t7 = pa.struct(fields)
#mylog.debug("t7 '%s'" % t7)
fixed_size_binary_small = np.full(size, "same_string_size_again_and_again")
fixed_size_binary_big = np.full(size, "same_string_size_again_and_again"*10)
fixed_size_binary_huge = np.full(size, "same_string_size_again_and_again"*1100)
#dec1_array = np.full(size, dec1)
#dec2_array = np.full(size, dec2)
#mylog.info("test %s" % dec1_array)
#mylog.info("test %s" % type(dec1_array))
#mylog.info("test %s" % decimal_list)
#sys.exit(0)
pd_SeriesSmall = pd.Series(fixed_size_binary_small)
pd_SeriesBig = pd.Series(fixed_size_binary_big)
pd_SeriesHuge = pd.Series(fixed_size_binary_huge)
mylog.debug("%s" % pprint.pformat(dir(pa)))
mylog.debug("first 4 decimals %s" % np_decimal_list[0:4])
mylog.debug("decimal.Context '%s'" % ctx)
uint8_list = np.arange( 1, size+1, 1, dtype=np.uint8)
int8_list = np.arange(-1,-size-1, -1, dtype=np.int8)
uint16_list = np.arange( 1, size+1, 1, dtype=np.uint16)
int16_list = np.arange(-1,-size-1, -1, dtype=np.int16)
uint32_list = np.arange( 1, size+1, 1, dtype=np.uint32)
int32_list = np.arange(-1,-size-1, -1, dtype=np.int32)
uint64_list = np.arange( 1, size+1, 1, dtype=np.uint64)
int64_list = np.arange(-1,-size-1, -1, dtype=np.int64)
bool_list = ( uint64_list % 2 == 0)
date32_list = np.arange( 1, size+1, 1, dtype=np.int32)
float16_list = np.linspace(0.0, 10.0, num=size, dtype=np.float16)
float32_list = np.linspace(0.0, 10.0, num=size, dtype=np.float32)
float64_list = np.linspace(0.0, 10.0, num=size, dtype=np.float64)
date64_list = np.full(size, now)
time32_ms_list = np.full(size, t4_ms)
time32_s_list = np.full(size, t4_s)
arr_uint8 = pa.array(uint8_list, pa.uint8())
arr_int8 = pa.array(int8_list, pa.int8())
arr_uint16 = pa.array(uint16_list, pa.uint16())
arr_int16 = pa.array(int16_list, pa.int16())
arr_uint32 = pa.array(uint32_list, pa.uint32())
arr_int32 = pa.array(int32_list, pa.int32())
arr_uint64 = pa.array(uint64_list, pa.uint64())
arr_int64 = pa.array(int64_list, pa.int64())
arr_float16 = pa.array(float16_list, pa.float16())
arr_float32 = pa.array(float32_list, pa.float32())
arr_float64 = pa.array(float64_list, pa.float64())
arr_bool = pa.array(bool_list, pa.bool_())
arr_date32 = pa.array(date32_list, pa.date32())
arr_date64 = pa.array(date64_list, pa.date64())
arr_time64_us = pa.array(np_time64_list, pa.time64("us"))
arr_time64_ns = pa.array(np_time64_ns_list, pa.time64("ns"))
arr_time32_ms = pa.array(time32_ms_list, pa.time32("ms"))
arr_time32_s = pa.array(time32_s_list, pa.time32("s"))
arr_timestamp_s = pa.array(date64_list, pa.timestamp("s"))
arr_timestamp_ms = pa.array(date64_list, pa.timestamp("ms"))
arr_timestamp_us = pa.array(date64_list, pa.timestamp("us"))
arr_timestamp_ns = pa.array(date64_list, pa.timestamp("ns"))
arr_timestamp_ns_tz1 = pa.array(date64_list, pa.timestamp("ns", tz='UTC'))
arr_timestamp_us_tz1 = pa.array(date64_list, pa.timestamp('us', tz='UTC'))
arr_timestamp_us_tz2 = pa.array(date64_list, pa.timestamp('us', tz='Europe/Paris'))
arr_string = pa.array(np_string_list, pa.string())
arr_string_big = pa.array(np_string_list_big, pa.string())
arr_string_huge = pa.array(np_string_list_huge, pa.string())
arr_binary = pa.array(np_string_list, pa.binary())
arr_binary_big = pa.array(np_string_list_big, pa.binary())
arr_binary_huge = pa.array(np_string_list_huge, pa.binary())
arr_fixed_size_binary_small = pa.array(pd_SeriesSmall,pa.binary(len(fixed_size_binary_small[0])))
arr_fixed_size_binary_big = pa.array(pd_SeriesBig, pa.binary(len(fixed_size_binary_big[0])))
arr_fixed_size_binary_huge = pa.array(pd_SeriesHuge, pa.binary(len(fixed_size_binary_huge[0])))
precision = 31
scale = 27
arr_decimals = pa.array(np_decimal_list, pa.decimal128(precision, scale))
#mylog.info("%s" % pprint.pformat(dir(pa)))
#mylog.info("%s" % pprint.pformat(dir(pa.types)))
mylog.debug("arr_time64_ns %s %s" % (arr_time64_ns, type(arr_time64_ns)))
mylog.debug("float16_list %s %s" % (float16_list, type(float16_list)))
mylog.debug("float32_list %s %s" % (float32_list, type(float32_list)))
mylog.debug("float64_list %s %s" % (float64_list, type(float64_list)))
mylog.debug("int8_list %s %s" % (int8_list, type(int8_list)))
mylog.debug("uint8_list %s %s" % (uint8_list, type(uint8_list)))
mylog.debug("int64_list %s %s" % (int64_list, type(int64_list)))
mylog.debug("uint64_list %s %s" % (uint64_list, type(uint64_list)))
mylog.debug("bool_list %s %s" % (bool_list, type(bool_list)))
mylog.debug("arr_fixed_size_binary %s %s" % (arr_fixed_size_binary_small, type(arr_fixed_size_binary_small)))
mylog.debug("arr_decimals %s %s" % (arr_decimals, type(arr_decimals)))
arrays.append(arr_uint8)
arrays.append(arr_int8)
arrays.append(arr_uint16)
arrays.append(arr_int16)
arrays.append(arr_uint32)
arrays.append(arr_int32)
arrays.append(arr_uint64)
arrays.append(arr_int64)
arrays.append(arr_float16)
arrays.append(arr_float32)
arrays.append(arr_float64)
arrays.append(arr_bool)
arrays.append(arr_date32)
arrays.append(arr_date64)
arrays.append(arr_time64_us)
arrays.append(arr_time64_ns)
arrays.append(arr_time32_ms)
arrays.append(arr_time32_s)
arrays.append(arr_timestamp_s)
arrays.append(arr_timestamp_ms)
arrays.append(arr_timestamp_us)
arrays.append(arr_timestamp_ns)
arrays.append(arr_timestamp_us_tz1)
arrays.append(arr_timestamp_us_tz1)
arrays.append(arr_timestamp_us_tz2)
arrays.append(arr_string)
arrays.append(arr_string_big)
arrays.append(arr_string_huge)
arrays.append(arr_binary)
arrays.append(arr_binary_big)
arrays.append(arr_binary_huge)
arrays.append(arr_fixed_size_binary_small)
arrays.append(arr_fixed_size_binary_big)
arrays.append(arr_fixed_size_binary_huge)
arrays.append(arr_decimals)
table = pa.Table.from_arrays(arrays,
column_names,
metadata={'a' :'pila de datos',
'b' :'esto es una b'})
del arrays
#table = table.drop(["c_timestamp_ns", "c_timestamp_us" , "c_timestamp_s", "c_timestamp_ms"])
#table = table.drop(["c_decimal128"])
return table
def read_test_table():
"""
example.arrow was a sample table generated using arrow java libraries
"""
try:
mylog.info("reading arrow java generated 'example.arrow'")
if os.path.exists("example.arrow"):
example_arrow = pq.read_table('example.arrow')
print ("%s" % example_arrow)
except pa.lib.ArrowIOError as e:
mylog.error("ArrowIOError %s " % e)
def do_all_fields_test(conn,
iDataBufferSize,
iChunkSize,
DB2_MAXROWS,
tablespace,
column_oriented,
drop_table,
db2_user,
table_with_dummy_data):
"""
Parameters
----------
conn : :class:`ibm_db.IBM_DBConnection`
iDataBufferSize : :obj:`int`
iChunkSize : :obj:`int`
tablespace : :obj:`str`
column_oriented : :obj:`int`
drop_table : :obj:`int`
"""
#filename = "test_parquet_table"
filename = "test_parquet_table".upper()
start = datetime.now()
MessageFile = os.path.join("log", "test_parquet.txt")
try:
mylog.info("deleting MessageFile '%s'" % MessageFile)
os.remove(MessageFile)
except OSError as e:
mylog.error("%s" % e)
if column_oriented == '1':
column_oriented = True
else:
column_oriented = False
if drop_table == '1':
drop_table = True
else:
drop_table = False
TempFilesPath = os.environ.get("TEMP", None)
mylog.debug("\nspclient_python.arrow_table_to_db2.__doc__ %s " %
spclient_python.arrow_table_to_db2.__doc__)
"""
Insert the data
"""
mylog.info("""
iDataBufferSize '%s'
iChunkSize '%s'
tablespace '%s'
TempFilesPath '%s'
DB2_MAXROWS %s
""" % (
"{:,}".format(iDataBufferSize),
"{:,}".format(iChunkSize),
tablespace,
TempFilesPath,
DB2_MAXROWS
))
monitor_thread = threading.Thread(target=monitor_load, args=(filename,) )
monitor_thread.start()
create_table = True
try:
load_result = spclient_python.arrow_table_to_db2(
conn,
MessageFile,
TempFilesPath,
iDataBufferSize,
200000,
iChunkSize,
DB2_MAXROWS,
table_with_dummy_data,
tablespace, # "TABLESPACE_NAME"
None, # "SCHEMA_NAME" aka CURRENT_USER
filename,
column_oriented, # column oriented row oriented, True or False
drop_table,
create_table)
mylog.info("load_result \n%s" % pprint.pformat(load_result))
bytes_allocated = load_result['bytes_allocated']
mylog.info("load_result bytes_allocated '%s'" % "{:,}".format(bytes_allocated))
mylog.info("load_result bytes_allocated '%s'" % humanfriendly.format_size(bytes_allocated, binary=True))
t_diff = relativedelta(datetime.now(), start)
seg = (t_diff.hours*60*60)+(t_diff.minutes*60)+t_diff.seconds
if seg == 0:
seg = 0.1
megs_per_seconds = bytes_allocated/(seg * 1024 * 1024)
mylog.info("Speed %5.5f M/seg" % megs_per_seconds)
retrieve_data_from_db2(conn, filename)
except Exception as e:
mylog.exception("%s %s" % (type(e), e))
def retrieve_data_from_db2(conn, filename):
"""Retrieve the data and display it
"""
sql_str = """
SELECT
*
FROM
"%s"
""" % filename
try:
mylog.info("executing \n%s\n" % sql_str)
stmt = ibm_db.exec_immediate(conn, sql_str)
describe_cols = spclient_python.describe_columns(stmt, True)
except Exception as e:
mylog.exception("Exception %s" % e)
return
mytable = Texttable()
dictionary = ibm_db.fetch_both(stmt)
if not dictionary:
mylog.warning("table '%s' is empty" % filename)
return
mytable.set_deco(Texttable.HEADER)
headers = []
allign = []
cols_width = []
cols_dtype = []
ignore_columns = ["c_fixed_size_binary_huge",
"c_fixed_size_binary_big",
"c_string_big", "c_string_huge",
"c_binary_big", "c_binary_huge"] # too big to display
if dictionary:
for key in dictionary.keys():
if isinstance(key, str):
if key in ignore_columns: # too big to display
mylog.info("column '%s'...skipping..not adding it to Texttable it wont fit on the screen len %d" % (
key,
len(dictionary[key])))
continue
headers.append(key)
allign.append("l")
cols_dtype.append("t")
cols_width.append(len(key))
mytable.header(headers)
mytable.set_cols_align(allign)
mytable.set_header_align(allign)
mytable.set_cols_width(cols_width)
mytable.set_cols_dtype(cols_dtype)
cont = 0
add_row = 0
once = True
while dictionary:
if (cont % 30000) == 0 or (cont < 5):
my_row = []
#print("%s" % type(dictionary["c_decimal128"]))
for key in dictionary.keys():
if isinstance(key, str):
if key in ignore_columns: # too big to display
mylog.debug("column '%s'...skipping" % key)
continue
my_row.append(dictionary[key])
for pos, len_ in enumerate(cols_width):
if len_ < len(str(my_row[pos])) :
cols_width[pos] = len(str(my_row[pos]))
mytable.add_row(my_row)
add_row += 1
try:
dictionary = ibm_db.fetch_both(stmt)
if dictionary:
if once:
once = False
c_bool = ibm_db.result(stmt, 'c_bool')
mylog.info("c_bool %s type '%s' " % (c_bool, ibm_db.field_type(stmt, 'c_bool')))
for key in ignore_columns:
mylog.info("reading special data '%s'" % key)
dummy_data = dictionary[key]
mylog.info("data len %8s column %-30s type '%s'" % (
"{:,}".format(len(dummy_data)),
key,
ibm_db.field_type(stmt, key)))
dummy_data = ibm_db.result(stmt, key)
mylog.info("reading by ibm_db.result data len %8s column %s" % (
"{:,}".format(len(dummy_data)),
key))
except Exception as e:
mylog.exception(
"""
Exception
%s
'%s'
""" % (type(e), str(e)))
dictionary = False
if cont > 100000:
break
if add_row >= 5: # only display 5 records...
dictionary = False
cont += 1
ibm_db.free_result(stmt)
mytable.set_cols_width(cols_width)
mylog.info("db2 table \"%s\" data \n%s" % (filename, mytable.draw()))
def read_df_from_db2(conn, metadata, filename):
key = list(metadata.keys())[0]
metadata_dict = json.loads(metadata[key])
columns = metadata_dict['columns']
index_columns = metadata_dict['index_columns']
columns_name_for_select=[]
for column in columns:
columns_name_for_select.append('"%s"' % column["field_name"])
column_str = ""
for column_name in columns_name_for_select:
column_str += column_name + ","
column_str = column_str[:-1]
#mylog.info("column_str %s" % column_str)
sql_str = '''
select
%s
from
"%s"
fetch first
10000 ROWS ONLY
''' % (column_str, filename)
dbapi_conn = ibm_db_dbi.Connection(conn)
df_db2 = pd.read_sql(sql_str, dbapi_conn, index_col=index_columns)
df_db2['c_boolean'] = df_db2['c_boolean'].astype('bool')
df_db2['c_float32'] = df_db2['c_float32'].astype('float32')
#df_db2['time'] = df_db2['time'].astype('time64[us]')
mylog.info("df_db2 from db2\n\n%s\n" % df_db2.head())
mylog.info("df_db2 from db2\n%s\n\n" % df_db2.dtypes)
def do_pandas_test(conn):
filename = "test_pandas_df"
df = create_df()
mylog.info("df \n%s\n\n" % df.head())
mylog.info("df \n%s\n\n" % df.dtypes)
table = pa.Table.from_pandas(df)
mylog.info("filename '%s'" % filename)
try:
TempFilesPath = os.environ.get("TEMP", None)
MessageFile = os.path.join("log", "test_pandas_df.txt")
column_oriented = False
drop_table = True
create_table = True
load_result = spclient_python.arrow_table_to_db2(
conn,
MessageFile,
TempFilesPath,
1000,
1000,
1000,
table,
None, #"Tablespace name
None, # Schema name
filename,
column_oriented, # column oriented=True row oriented =False
drop_table,
create_table)
mylog.info("load_result \n%s" % load_result)
read_df_from_db2(conn, table.schema.metadata, filename)
except Exception as e:
mylog.error("%s %s" % (type(e), e))
def connect_to_db2(data_read_ini):
userid = data_read_ini["DB2_USER"]
passw = data_read_ini["DB2_PASSWORD"]
connecting_str = """
UID={DB2_USER};
PWD={DB2_PASSWORD};
DATABASE={DB2_DATABASE};
DBALIAS={DB2_ALIAS};
HOSTNAME={DB2_HOSTADDR};
PORT={DB2_PORT};
PROTOCOL={DB2_PROTOCOL};
PROGRAMNAME=Python_ibm_db_test;
PROGRAMID=ProgramId_ibm_db_test;
CLIENTAPPLNAME=Client_ibm_db_test;
CLIENTUSERID=ClientUserID_ibm_db_test;
CONNECTTIMEOUT=10;
QueryTimeout=10;
AllowGetDataLOBReaccess=1;
""".format(**data_read_ini)
connecting_str = connecting_str.replace("\n", "")
mylog.debug("connecting %s " % connecting_str)
try:
conn = ibm_db.connect(connecting_str, userid, passw)
except Exception as e:
mylog.error("Exception %s" % e)
return None
ibm_db.autocommit(conn, ibm_db.SQL_AUTOCOMMIT_ON)
return conn
if __name__ == "__main__":
data_read_ini = read_ini()
conn = connect_to_db2(data_read_ini)
if conn is None:
sys.exit(0)
read_test_table()
table_with_dummy_data_small = create_dummy_data_all_fields(5)
mylog.debug("%s" % pprint.pformat(dir(table_with_dummy_data_small)))
pool = pa.default_memory_pool()
bytes_allocated = pool.bytes_allocated()
mylog.info("bytes_allocated %s" % "{:,}".format(bytes_allocated))
mylog.info("bytes_allocated '%s'" % humanfriendly.format_size(bytes_allocated, binary=True))
table_with_dummy_data = create_dummy_data_all_fields(int(data_read_ini["TEST_SIZE"]))
bytes_allocated = pool.bytes_allocated()
mylog.info("bytes_allocated %s" % "{:,}".format(bytes_allocated))
mylog.info("bytes_allocated '%s'" % humanfriendly.format_size(bytes_allocated, binary=True))
mylog.debug("table_with_dummy_data_small %s" % table_with_dummy_data_small)
#mylog.info("table_with_dummy_data.schema \n%s" % table_with_dummy_data.schema)
mylog.info("table_with_dummy_data_small num_rows %s num_columns %s" % (
"{:,}".format(table_with_dummy_data_small.num_rows),
table_with_dummy_data_small.num_columns))
for key in data_read_ini.keys():
if key.upper().startswith("SPCLIENT_PYTHON"):
os.environ[key] = data_read_ini[key]
mylog.debug ("'%s'" % data_read_ini["SPCLIENT_PYTHON_LOG_COLUMN"])
mylog.debug ("'%s'" % pprint.pformat(data_read_ini))
"""
All fields type test
"""
mylog.debug("%s" % pprint.pformat(data_read_ini))
spclient_python.set_mylog(mylog.info)
do_all_fields_test(conn,
int(data_read_ini["DB2_IDATABUFFERSIZE"]),
int(data_read_ini["DB2_ICHUNKSIZE"]),
int(data_read_ini["DB2_MAXROWS"]),
data_read_ini["DB2_TABLESPACE"],
data_read_ini["DB2_COLUMN_ORIENTED"],
data_read_ini["DB2_DROPTABLE"],
data_read_ini["DB2_USER"],
table_with_dummy_data_small)
'''
do_all_fields_test(conn,
int(data_read_ini["DB2_IDATABUFFERSIZE"]),
int(data_read_ini["DB2_ICHUNKSIZE"]),
int(data_read_ini["DB2_MAXROWS"]),
data_read_ini["DB2_TABLESPACE"],
data_read_ini["DB2_COLUMN_ORIENTED"],
data_read_ini["DB2_DROPTABLE"],
data_read_ini["DB2_USER"],
table_with_dummy_data)
'''
"""
Another test with pandas dataframe
"""
#do_pandas_test(conn)