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odbc_test.py
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import pyodbc
import json
import array
con_str ="DRIVER={ODBC Driver 18 for SQL Server};SERVER=10.177.3.78;DATABASE=vectordb;UID=sa;PWD=1_SQLPerf;LongAsMax=yes;Connect Timeout=30;TrustServerCertificate=Yes;LongAsMax=yes;"
cxn = pyodbc.connect(con_str)
cur = cxn.cursor()
cxn.autocommit = True
# Integer
"""
hndl = cur.prepareStatement("declare @v int = ?; SELECT @v as id")
cur.executePreparedStatement(hndl, 1)
cur.executePreparedStatement(hndl, 2)
"""
# Small Vector (string)
"""
hndl = cur.prepareStatement("declare @v vector(1) = ?; SELECT @v as id")
cur.executePreparedStatement(hndl, '[1]')
print(cur.fetchall())
cur.executePreparedStatement(hndl, '[2]')
print(cur.fetchall())
"""
#small vector (json)
"""
hndl = cur.prepareStatement("declare @v vector(1) = ?; SELECT @v as id")
arr1: list[float] = [1.0]
cur.executePreparedStatement(hndl, json.dumps(arr1))
cur.fetchall()
arr2: list[float] = [2.0]
cur.executePreparedStatement(hndl, json.dumps(arr2))
cur.fetchall()
"""
# Execute (Existing Method
"""
qstr = "declare @v vector(1) = ?; SELECT @v as id"
cur.execute(qstr, json.dumps([1.0]))
cur.fetchall()
cur.execute(qstr, json.dumps([2.0]))
cur.fetchall()
"""
vector_query = f"""
declare @v vector(768) = ?;
select t.id from vector_search(
table = benchmark.vector_768 AS t,
column = [vector],
similar_to = @v,
metric = 'cosine',
top_n = 100
) AS s
order by t.id
"""
vector_str = "[5.9977955e-001,-3.8075708e-002,1.9585741e-001,1.5361838e-001,-3.0363151e-001,-1.5656266e-001,8.5628882e-002,-3.2310346e-001,4.5814607e-001,3.7439802e-001,-7.9910809e-001,-3.8817456e-001,-3.4488007e-001,-5.1276213e-001,-5.5713862e-001,8.1733841e-001,3.6187190e-001,1.2260879e-001,-1.8463045e-001,4.1962963e-001,-1.5076199e-001,4.4040194e-001,6.6226476e-001,2.7633250e-001,-2.2730359e-001,-5.3684306e-001,-6.2783718e-001,5.8355898e-001,1.3336404e-001,2.6816073e-001,1.6654356e-001,1.8393926e-001,-1.1788813e-001,7.4006051e-001,-4.1048962e-001,4.6749231e-001,-1.0577632e-001,3.8179988e-001,3.9497682e-001,7.6636061e-002,7.4511208e-002,2.1377610e-001,3.2279518e-001,3.4711295e-001,1.0487367e-001,-4.5121048e-002,-4.9846119e-001,7.1444109e-002,-2.8534451e-001,5.2747842e-002,-5.7636791e-001,-6.6837937e-001,1.9100878e-001,-5.1111281e-002,-2.6745495e-001,5.3156167e-001,-1.8491144e-001,9.8373878e-001,1.4814475e-001,1.3484030e-002,3.6502352e-001,2.0602469e-001,-6.2730066e-002,3.4110883e-001,3.2216419e-002,1.9145665e-001,1.9704662e-001,4.7838247e-001,-4.4469081e-002,-4.3953348e-002,-1.0124495e-002,1.0318197e+000,1.6857216e-002,5.1048142e-001,-3.1624679e-002,-4.1736302e-001,1.4792714e-001,3.1410402e-001,1.8609481e-001,5.3387359e-002,-8.4357988e-003,-4.7007611e-001,-3.8370860e-001,-2.2109731e-001,-2.6045308e-001,1.6258748e-001,1.6759826e-001,1.1862870e-001,5.9571642e-002,4.4171327e-001,1.7764464e-001,2.2933428e-001,2.9364315e-001,-3.7274447e-001,4.2192522e-001,6.8135577e-001,4.0613838e-002,1.3984668e-001,-7.7681110e-004,-2.7932508e-002,2.4264689e-001,-3.1591243e-001,-3.6703861e-001,6.8895006e-001,3.3070233e-001,-2.6538917e-001,-4.1471191e-002,1.4756104e-001,2.7742907e-001,6.3011956e-001,5.5356425e-001,-3.1703312e-002,4.0938038e-001,7.4308008e-002,1.4264560e-001,-4.6318102e-001,4.9717954e-001,-1.3379550e-001,1.1097339e-001,-8.9173609e-001,3.1040630e-001,-1.4062203e-002,-1.4396366e-001,-2.9340780e-001,5.7858929e-002,3.3102441e-001,7.6907998e-001,-1.0137051e+000,4.3809927e-001,6.7284232e-001,-3.0731526e-001,4.6747380e-001,4.9482310e-001,4.3235826e-001,-1.3134950e-001,4.4986668e-001,3.7593311e-001,7.1316920e-002,9.5404796e-002,-2.8968650e-001,-5.9776228e-002,1.9763045e-001,2.5582319e-001,1.0269628e+000,1.6949998e-001,2.0118529e-001,5.1532570e-002,2.1545807e-001,-1.1531670e-001,3.1187207e-001,2.5224119e-001,-2.5006336e-001,-3.6902225e-001,4.6877959e-001,-6.3426304e-001,3.3982132e-002,-2.5607440e-001,-2.8416577e-001,-1.9679101e-001,3.9122471e-001,8.0807590e-001,2.7020726e-001,-5.1573622e-003,-2.9305041e-001,-5.9449136e-002,2.8194774e-002,4.0674752e-001,5.4605007e-001,3.3612061e-001,1.5536666e-001,-3.0526966e-001,4.2963896e-002,-2.7714127e-001,-1.7953110e-001,-4.2495248e-003,4.9398157e-001,-2.9836226e-001,-5.2178305e-001,5.0255471e-001,4.4807804e-001,3.1841487e-001,4.7542717e-002,-1.7926858e-001,-3.4188426e-001,3.6179882e-001,-8.1805386e-002,4.6926817e-001,-1.1807907e-001,-5.7628286e-001,3.4132987e-001,2.4208808e-001,-1.5096105e-002,1.2200150e+000,-6.9691187e-001,-2.3239252e-001,1.1430018e-001,-1.5628126e-001,1.5654638e-001,-4.9177459e-001,-1.5728390e-001,5.2605045e-001,-4.3521211e-001,-1.4463644e-001,2.6662213e-001,8.3560461e-001,-7.4553794e-001,-9.7848065e-002,6.2875831e-001,-1.0004760e-001,-2.4288870e-001,2.7162436e-001,1.1195856e-001,-2.0287997e-001,7.5073592e-002,-2.5612664e-001,-3.5917190e-001,4.0668604e-001,-7.4388623e-002,4.6924800e-001,-2.3662712e-001,2.1187429e-001,7.0933211e-001,4.8574588e-001,2.8949067e-001,1.1250265e-002,2.6971388e-001,-3.2266974e-001,-7.7331543e-001,1.7966437e-001,2.6881918e-001,4.7858280e-001,3.0053920e-001,-3.2679643e-002,-4.5157415e-001,-2.1067359e-001,1.4211331e-001,-1.9628952e-001,4.6006081e-001,-3.8028546e-002,-2.8824431e-001,5.1126379e-001,6.5087241e-001,5.7835143e-002,3.0018547e-001,4.6559837e-001,-3.2447994e-001,6.5223187e-001,8.2031989e-001,-7.8532100e-002,1.4841558e-001,-1.5741915e-001,7.8207862e-001,-6.5942593e-002,6.5553606e-001,-3.3507377e-001,3.8827053e-001,6.3852024e-001,1.6861190e-001,1.7676486e-001,4.4269156e-002,2.4591400e-001,1.0022594e-001,5.4712653e-001,1.9257501e-001,-1.3076656e-001,-1.6166791e-001,8.4165514e-002,6.1974359e-001,3.5056633e-001,3.2450485e-001,1.4374004e-001,-2.9632139e-001,3.1888939e-002,-1.9975893e-001,-1.1092533e-003,2.3457788e-002,-1.4073889e-001,-1.4822966e-001,-4.3171090e-001,5.3009450e-001,6.0500801e-002,-2.4954507e-001,1.6182812e-002,-2.1229894e-001,-1.5276164e-001,2.2978823e-001,1.3562937e-001,1.0871315e-001,7.3888429e-002,-3.5912716e-001,5.7802141e-001,6.3001597e-001,6.7393541e-001,-6.8759251e-001,6.0650969e-001,6.2095922e-001,-2.1936197e-002,2.0380373e-001,-1.5098572e-002,-2.4615109e-001,-3.1543616e-002,-3.9931974e-001,-2.2979309e-001,6.8612464e-002,-3.0120203e-001,-9.3151465e-002,2.0634980e-001,1.9683771e-001,-1.5940672e-001,-4.9649063e-002,4.3932828e-001,-2.2712477e-001,-2.3230952e-001,6.9776499e-001,5.3889418e-001,6.8848026e-001,2.5468016e-001,-2.5665098e-001,9.7770602e-002,5.3905880e-001,-2.6668018e-001,2.3387514e-001,-4.1181713e-001,2.8988600e-001,6.61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"""
hndl = cur.prepareStatement(vector_query)
cur.executePreparedStatement(hndl, vector_str)
cur.executePreparedStatement(hndl, vector_str)
"""
vector_arr = 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#print("vector_arr " + str(id(vector_arr)) + " vector_arr2 " + str(id(vector_arr2)))
#vector_arr = vector_arr2
#print("vector_arr " + str(id(vector_arr)) + " vector_arr2 " + str(id(vector_arr2)))
hndl = cur.prepareStatement(vector_query)
cur.executePreparedStatement(hndl, json.dumps(vector_arr))
cur.executePreparedStatement(hndl, json.dumps(vector_arr2))
cur.executePreparedStatement(hndl, json.dumps(vector_arr))
cur.executePreparedStatement(hndl, json.dumps(vector_arr2))
cur.executePreparedStatement(hndl, json.dumps(vector_arr))
cur.executePreparedStatement(hndl, json.dumps(vector_arr2))
cur.executePreparedStatement(hndl, json.dumps(vector_arr))
cur.executePreparedStatement(hndl, json.dumps(vector_arr2))
cur.executePreparedStatement(hndl, json.dumps(vector_arr))
cur.executePreparedStatement(hndl, json.dumps(vector_arr2))
cur.executePreparedStatement(hndl, json.dumps(vector_arr))
cur.executePreparedStatement(hndl, json.dumps(vector_arr2))
cur.executePreparedStatement(hndl, json.dumps(vector_arr))
cur.executePreparedStatement(hndl, json.dumps(vector_arr2))
cur.executePreparedStatement(hndl, json.dumps(vector_arr))
cur.executePreparedStatement(hndl, json.dumps(vector_arr2))
cur.executePreparedStatement(hndl, json.dumps(vector_arr))
cur.executePreparedStatement(hndl, json.dumps(vector_arr2))
cur.executePreparedStatement(hndl, json.dumps(vector_arr))
cur.executePreparedStatement(hndl, json.dumps(vector_arr2))
cur.executePreparedStatement(hndl, json.dumps(vector_arr))
cur.executePreparedStatement(hndl, json.dumps(vector_arr2))
cur.executePreparedStatement(hndl, json.dumps(vector_arr))