openinx

import time
import pymysql
import prettytable
import itertools
import traceback
import ConfigParser
from nepo.common import utils
import nepo.web.constant as web_const

openinx

conn = pymysql.connect(user='root',host='127.0.0.1', port=3306, db='test')
try:
    cursor = conn.cursor(pymysql.cursors.SSCursor)
    cursor.execute('select * from sbtest') 
    while True:
        row = cursor.fetchone()
        if not row:
            break
        print row
finally:

openinx

import pymysql
from contextlib import contextmanager
#from contextlib import contextmanager


@contextmanager
def create_dict_cursor():
    with pymysql.connect(user='root', passwd='goodboy', host='127.0.0.1', cursorclass=pymysql.cursors.DictCursor) as cursor:
        yield cursor

openinx

    def assertDictMatch(self, d1, d2, approx_equal=False, tolerance=0.001):
        """Assert two dicts are equivalent.

        This is a 'deep' match in the sense that it handles nested
        dictionaries appropriately.

        NOTE:

            If you don't care (or don't know) a given value, you can specify
            the string DONTCARE as the value. This will cause that dict-item

openinx

#!/usr/bin/python

import sys
import time
import datetime
import re
import pymysql
import pymysql.cursors

#   create table `ycsb`(

openinx

spark-sql> select * from default.test_table_1;
23/12/26 13:37:52 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0) (core-1-2.emr-967e350d6501c1edbb51.cn-beijing.emr-volces.com executor 1): java.lang.UnsupportedOperationException: Unsupported type: UTF8String
	at org.apache.iceberg.arrow.vectorized.ArrowVectorAccessor.getUTF8String(ArrowVectorAccessor.java:81)
	at org.apache.iceberg.spark.data.vectorized.IcebergArrowColumnVector.getUTF8String(IcebergArrowColumnVector.java:138)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760)
	at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:364)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890)
	at org.apache.spark.rdd.RDD.$anonfun$mapParti