Question

BLOB数据是一个XML片段，目前在数据库中看起来像这样

import numpy as np
import types
from timeit import repeat

prom={np.dtype(np.int32): np.dtype(np.int64), np.dtype(float): np.dtype(float)}

def RI(k, N, dt, top=100):
    return np.random.randint(0, top if top else N, (k, N)).astype(dt)

def RA(k, N, dt, top=None):
    return np.add.outer(np.zeros((k,), int), np.arange(N)%(top if top else N)).astype(dt)

def RU(k, N, dt, top=100):
    return (np.random.random((k, N))*(top if top else N)).astype(dt)

def data(k, N_b, N_e, dt_b, dt_e, b_fun=RI, e_fun=RA):
    b = list(b_fun(k, N_b, dt_b))
    e = list(e_fun(k, N_e, dt_e))
    return b, e

def f_vander(b, e):
    return np.vander(b, len(e), increasing=True)

def f_bc_b(b, e):
    return b[:, None]**e

def f_bc_e(b, e):
    return np.ascontiguousarray((b**e[:, None]).T)

def f_ma(b, e):
    out = np.empty((len(b), len(e)), prom[b.dtype])
    out[:, 0] = 1
    np.multiply.accumulate(np.broadcast_to(b, (len(e)-1, len(b))), axis=0, out=out[:, 1:].T)
    return out

def f_nnc(b, e):
    out = np.empty((len(b), len(e)), prom[b.dtype])
    out[:, 0] = 1
    out[:, 1:] = b[:, None]
    np.multiply.accumulate(out[:, 1:], out=out[:, 1:], axis=1)
    return out

def f_out_e_1(b, e):
    out = np.empty((len(b), len(e)), b.dtype)
    out[:, 0] = 1
    out[:, 1] = b
    out[:, 2] = c = b*b
    for i in range(3, len(e)):
        c*=b
        out[:, i] = c
    return out

def f_out_e_2(b, e):
    out = np.empty((len(b), len(e)), b.dtype)
    out[:, 0] = 1
    out[:, 1] = b
    out[:, 2] = b*b
    for i in range(3, len(e)):
        out[:, i] = out[:, i-1] * b
    return out

def f_safe_e_1(b, e):
    out = np.empty((len(b), len(e)), prom[b.dtype])
    out[:, 0] = 1
    out[:, 1] = b
    out[:, 2] = c = (b*b).astype(prom[b.dtype])
    for i in range(3, len(e)):
        c*=b
        out[:, i] = c
    return out

def f_safe_e_2(b, e):
    out = np.empty((len(b), len(e)), prom[b.dtype])
    out[:, 0] = 1
    out[:, 1] = b
    out[:, 2] = b*b
    for i in range(3, len(e)):
        out[:, i] = out[:, i-1] * b
    return out

def f_bc_e_cheat(b, e):
    return (b**e[:, None]).T

for params in [(100, 5000, 4, np.int32, np.int32),
               (100, 5000, 8, np.int32, np.int32),
               (100, 5000, 4, float, np.int32),
               (100, 5000, 8, float, np.int32)]:
    k = params[0]
    dat = data(*params)
    ref = f_vander(dat[0][0], dat[1][0])
    print('rep={} n_b={} n_e={} b_tp={} e_tp={}'.format(*params))
    for name, func in list(globals().items()):
        if not name.startswith('f_') or not isinstance(func, types.FunctionType):
            continue
        try:
            assert np.allclose(ref, func(dat[0][0], dat[1][0]))
            if not func(dat[0][0], dat[1][0]).flags.c_contiguous:
                print('cheat', end=' ')
            print("{:16s}{:16.8f} ms".format(name[2:], np.min(repeat(
                'f(b.pop(), e.pop())', setup='b, e = data(*p)', globals={'f':func, 'data':data, 'p':params}, number=k)) * 1000 / k))
        except:
            print("{:16s} apparently failed".format(name[2:]))

我需要通过删除年份来更新如下所示。

    <lrs-conv end-page="34" runhead="LMI v BAULDERSTONE" series="NSWLR" start-page="31" version="1" volume="(2001) 53">

我有大约1000条BLOB数据记录需要同样更新。所以我认为UPDATE SQL脚本可能会有所帮助。

Answer 1

我尝试了下面的脚本，但它只是让我只更新数据库中的一条记录，因为substr的参数不断更改数据库中的其他记录。我想更改SQL，以便它可以为所有记录更新BLOB XML中的卷。

Update FRAGMENT F
       set F.FRAGMENT_DATA = REPLACE ((select DBMS_LOB.SUBSTR(FRAGMENT_DATA) 
           from 
         FRAGMENT where OBJECT_ID = '5037087'
         and fragment_type_id = 77 and doctype_id = 29),
         (select Dbms_lob.substr(FRAGMENT_DATA,7,106) from Fragment  where 
         OBJECT_ID = '5037087'
         and fragment_type_id = 77 and doctype_id = 29),
         '')
         where OBJECT_ID = '5037087'
and fragment_type_id = 77 and doctype_id = 29

如何使用SQL更新BLOB数据。我正在使用oracle 8.1

1 个答案: