def series_mod(**kwargs):
## 画图类型
_picType = yamlDict.get('picType')
## hive查询数据
_hiveDB = lengthline.hiveDB or hive_conn.hiveDB
_hiveTable = lengthline.hiveTable or hive_conn.hiveTable
## wds数据分支名称
_branchName = kwargs.get('branchName')
## 获取索引列表
_textTagList = yamlDict.get(_branchName).get('textTagList')
_divUnit = yamlDict.get(_branchName).get('divUnit') or 1
_filterKeyList = [w.get('wds') for w in _textTagList]
## HQL查询语句
if len(_filterKeyList) == 1:
_HQL = "SELECT wds,year,value FROM `{}`.`{}` WHERE wds='{}' ORDER BY year".format(
_hiveDB, _hiveTable, _filterKeyList[0])
elif len(_filterKeyList) > 1:
_HQL = "SELECT wds,year,value FROM `{}`.`{}` WHERE wds IN {} ORDER BY year".format(
_hiveDB, _hiveTable, tuple(_filterKeyList))
## 数据查询
_resultList = spark_hive_query(HQL=_HQL)
## 获取查询数据年份列表并去重不排序
_yearList = [x.year for x in _resultList]
_yearList = list_uniq(_yearList)
## 计算series列表
_seriesList = []
for _x in _textTagList:
_perList = [
per_list(_y, _x.get('wds'), _resultList, _divUnit)
for _y in _yearList
]
_seriesList.append({
'name': _x.get('name'),
'type': _picType,
'data': _perList
})
## 返回数据
return {'year': _yearList, 'series': _seriesList}
def main():
## 获取yaml自定义画图数据
textTagList = yamlDict.get('textTagList')
colorList = yamlDict.get('colorList')
yUnit = yamlDict.get('yUnit')
divUnit = yamlDict.get('divUnit')
picType = yamlDict.get('picType')
##获取hive连接信息
hiveDB = portTEU.hiveDB or hive_conn.hiveDB
hiveTable = portTEU.hiveTable or hive_conn.hiveTable
## 数据列表
dataList = []
for w in textTagList:
## 查询条件wds
filterKeys = w.get('code')
## 查询语句
HQL = "SELECT year,value FROM {db}.{tb} WHERE wds='{fk}' \
AND year=(SELECT MAX(year) FROM {db}.{tb} WHERE wds='{fk}' AND value!=0)".format(
db=hiveDB, tb=hiveTable, fk=filterKeys)
## Hive查询
result = spark_hive_query(HQL=HQL)
## 查询结果换算
totalValue = round(result[0][1] / divUnit, 2)
## 查询结果添加到数据列表
dataList.append({'name': w.get('name'), 'value': totalValue})
## 定义排序索引的键值
sortKey = 'value'
## 取出画图列表
drawList = semicircle(dataList, sortKey)
##标签列表
labelList = [x.get('name') for x in drawList]
## 生成输出字典
outputDict = {'color': colorList, 'label': labelList, 'data': drawList}
## 转json字符串,不转码
outputStr = json.dumps(outputDict, ensure_ascii=False)
## 存储结果到mysql数据库
mysql_update(dataLabel=portTEU.label, dataValues=outputStr)
def series_mod(**kwargs):
## 通过参数获取分支名称
_branchName = kwargs.get('branchName')
## 获取对应分支数据在yaml数据中
_textTagList = yamlDict.get(_branchName).get('textTagList')
_divUnit = yamlDict.get(_branchName).get('divUnit') or 1
_filterKeyList = [w.get('wds') for w in _textTagList]
## HQL查询语句
if len(_filterKeyList) == 1:
_HQL = "SELECT wds,year,value FROM `{}`.`{}` WHERE wds='{}' ORDER BY year".format(
hiveDB, hiveTable, _filterKeyList[0])
elif len(_filterKeyList) > 1:
_HQL = "SELECT wds,year,value FROM `{}`.`{}` WHERE wds IN {} ORDER BY year".format(
hiveDB, hiveTable, tuple(_filterKeyList))
## 结果查询
_resultList = spark_hive_query(HQL=_HQL)
## 获取年份列表并去重
_yearList = [x.year for x in _resultList]
_yearList = list_uniq(_yearList)
## 统计series列表
_seriesList = []
for x in _textTagList:
_perList = [
per_list(y, x.get('wds'), _resultList, _divUnit) for y in _yearList
]
_seriesList.append({
'name': x.get('name'),
'type': picType,
'data': _perList
})
## 返回年份列表和series列表
return {'year': _yearList, 'series': _seriesList}
def main():
## 获取yaml数据
textTagList = yamlDict.get('textTagList')
colorMin = yamlDict.get('colorMin')
colorMax = yamlDict.get('colorMax')
titleName = yamlDict.get('titleName')
subName = yamlDict.get('subName')
subLink = yamlDict.get('subLink')
yUnit = yamlDict.get('yUnit')
divUnit = yamlDict.get('divUnit')
picType = yamlDict.get('picType')
##获取hive连接信息
hiveDB = railwayfreight.hiveDB or hive_conn.hiveDB
hiveTable = railwayfreight.hiveTable or hive_conn.hiveTable
## 关键词列表
indexList = [w.get('name') for w in textTagList]
## 坐标列表
axisList = [jsonDict.get(x) for x in indexList]
## 坐标输出字典
axisDict = dict(zip(indexList, axisList))
## 数据列表
dataList = []
yearList = []
for w in textTagList:
filterKeys = w.get('code')
HQL = "SELECT year,value FROM {db}.{tb} WHERE wds='{fk}' \
AND year=(SELECT MAX(year) FROM {db}.{tb} WHERE wds='{fk}' AND value!=0)".format(
db=hiveDB, tb=hiveTable, fk=filterKeys)
result = spark_hive_query(HQL=HQL)
totalValue = round(result[0][1] / divUnit, 2)
yearList.append(result[0][0])
dataList.append({'name': w.get('name'), 'value': totalValue})
## 年份列表去重
yearList = list(set(yearList))
## 修正标题名称
if len(yearList) == 1:
titleName = str(
max(yearList)) + '年' + titleName + '(单位: ' + yUnit + ')'
else:
titleName = str(min(yearList)) + '-' + str(
max(yearList)) + '年' + titleName + '(单位: ' + yUnit + ')'
## 取最大值和最小值
_max = max(x.get('value') for x in dataList)
_min = min(x.get('value') for x in dataList)
## 生成输出字典
outputDict = {
'name': titleName,
'subname': subName,
'sublink': subLink,
'colorMax': colorMax,
'colorMin': colorMin,
'max': _max,
'min': _min,
'axis': axisDict,
'data': dataList
}
## 转json字符串,不转码
outputStr = json.dumps(outputDict, ensure_ascii=False)
## 存储结果到mysql数据库
mysql_update(dataLabel=railwayfreight.label, dataValues=outputStr)
def main():
## 定义相关标签及输出格式
textTagList = yamlDict.get('textTagList')
legendList = [x.get('name') for x in textTagList]
colorList = yamlDict.get('colorList')
titleName = yamlDict.get('titleName')
yUnit = yamlDict.get('yUnit')
divUnit = yamlDict.get('divUnit') or 1
picType = yamlDict.get('picType')
## 定义数据库名称，表名称及查询语句
## 备注: 测试环境性能太差，为节省时间，这里直接查询出运输业人数总数据。
hiveDB = lengthtraveller.hiveDB or hive_conn.hiveDB
hiveTable = lengthtraveller.hiveTable or hive_conn.hiveTable
## 设置一个列表收集wds值
keyList = [e.get('wds') for e in textTagList]
## wds集合转元组用于HQL查询
keyTuple = tuple(keyList)
## HQL查询语句
if len(keyTuple) == 1:
HQL = "SELECT wds,year,value FROM `{}`.`{}` WHERE wds='{}'".format(
hiveDB, hiveTable, keyTuple[0])
elif len(keyTuple) > 1:
HQL = "SELECT wds,year,value FROM `{}`.`{}` WHERE wds IN {}".format(
hiveDB, hiveTable, keyTuple)
## 获取查询结果，输出列表，详情查看functions脚本spark_hive_query模块
resultList = spark_hive_query(HQL=HQL)
## 获取年份列表
yearList = [y.year for y in resultList]
## 年份列表去重
yearList = list_uniq(yearList)
## 年份类别排序
list.sort(yearList)
## 定义series列表
seriesList = []
for x in textTagList:
## 获取dfwds.code的数据列表
perList = [
per_list(y, x.get('wds'), resultList, divUnit) for y in yearList
]
## 数据汇总列表修正(汇总列表-dfwds.code列表)
seriesList.append({
'name': x.get('name'),
'type': picType,
'data': perList
})
## 定义输出格式(字典)
outputDict = {
'title': titleName,
'legend': legendList,
'color': colorList,
'xlabel': yearList,
'yname': yUnit,
'series': seriesList
}
## 转json字符串,不转码
outputStr = json.dumps(outputDict, ensure_ascii=False)
## 存储结果到mysql数据库
mysql_update(dataLabel=lengthtraveller.label, dataValues=outputStr)
def main():
## 读取yaml数据
textTagList = yamlDict.get('textTagList')
colorList = yamlDict.get('colorList')
titleName = yamlDict.get('titleName')
yUnit = yamlDict.get('yUnit')
divUnit = yamlDict.get('divUnit') or 1
## 获取hive连接信息
hiveDB = traffic.hiveDB or hive_conn.hiveDB
hiveTable = traffic.hiveTable or hive_conn.hiveTable
## 定义输出的数据列表
dataList = []
for t in textTagList:
## 总数data列表
masterList = []
totalValue = 0
for w in t.get('total'):
filterKeys = w.get('wds')
## hive查询语句
HQL = "SELECT year,value FROM {db}.{tb} WHERE wds='{fk}' \
AND year=(SELECT MAX(year) FROM {db}.{tb} WHERE wds='{fk}' AND value!=0)".format(
db=hiveDB, tb=hiveTable, fk=filterKeys)
result = spark_hive_query(HQL=HQL)
totalValue += round(float(result[0][1]) / divUnit, 2)
## 获取数据年份
year = str(result[0][0]) + '年'
## 总数data列表
masterList.append({'name': w.get('name'), 'value': totalValue})
## 总数列表其他数据
name = year + t.get('name') + yUnit
radius = t.get('master').get('radius')
center = t.get('master').get('center')
## 总数列表
dataList.append({
'name': name,
'radius': radius,
'center': center,
'data': masterList
})
## 具体项列表
branchList = []
## 剩余值
remainValue = totalValue
for w in t.get('specific'):
filterKeys = w.get('wds')
HQL = "SELECT year,value FROM {db}.{tb} WHERE wds='{fk}' \
AND year=(SELECT MAX(year) FROM {db}.{tb} WHERE wds='{fk}' AND value!=0)".format(
db=hiveDB, tb=hiveTable, fk=filterKeys)
specValue = round(
float(spark_hive_query(HQL=HQL)[0][1]) / divUnit, 2)
remainValue -= specValue
branchList.append({'name': w.get('name'), 'value': specValue})
## 修正由四舍五入导致的误差
if remainValue <= 0:
remainValue = 0
branchList.append({'name': '其他', 'value': round(remainValue, 2)})
name = year + t.get('name') + yUnit
radius = t.get('branch').get('radius')
center = t.get('branch').get('center')
dataList.append({
'name': name,
'radius': radius,
'center': center,
'data': branchList
})
outputDict = {
'name': titleName,
'label': legend(),
'color': colorList,
'data': dataList
}
## 转json字符串,不转码
outputStr = json.dumps(outputDict, ensure_ascii=False)
## 存储结果到mysql数据库
mysql_update(dataLabel=traffic.label, dataValues=outputStr)