初始化项目

spark/common/Constants.py

+
+
+# mysql 相关参数
+MY_MYSQL_DRIVER = 'org.mariadb.jdbc.Driver'
+MY_MYSQL_URL = 'jdbc:mysql://hadoop1:3306/wanjia?useSSL=false'
+MY_MYSQL_USER = 'root'
+MY_MYSQL_PASSWORD = '123'
+
+# save 相关参数
+'''
+    :param mode: specifies the behavior of the save operation when data already exists.
+    * ``append``: Append contents of this :class:`DataFrame` to existing data.
+    * ``overwrite``: Overwrite existing data.
+    * ``ignore``: Silently ignore this operation if data already exists.
+    * ``error`` or ``errorifexists`` (default case): Throw an exception if data already exists.
+    '''
+SAVE_MODE_OVERWRITE = 'overwrite'
+SAVE_MODE_APPEND = 'append'
+SAVE_MODE_IGNORE = 'ignore'
+SAVE_MODE_ERROR = 'error'
+
+HDFS_PATH = 'hdfs://hadoop1:9000/wanjia'
\ No newline at end of file

spark/dependencies.py

 #!/usr/local/bin/python
-import hashlib
 import json
 import sys
+
+from common import Constants
 from pyspark.sql import SparkSession
 from pyspark.sql.types import StringType
-# import os
-import pymysql
-
-# os.system("pip install pyspark")
-def getMySqlConnect():
-    # 连接数据库
-    conn = pymysql.connect(
-        host="hadoop1",  # 连接主机名,也可以用ip地址，例如127.0.0.1
-        user="root",  # 连接用户名
-        passwd="123",  # 用户密码
-        db="wanjia",  # 要连接的数据库名
-        charset="utf8",  # 指定编码格式
-        autocommit=True,  # 如果插入数据，， 是否自动提交? 和conn.commit()功能一致。
-    )
-    return conn
-
-def getRecordByIdResultT1(id):
-    conn = getMySqlConnect()
-    # 创建游标对象,用来给数据库发送sql语句
-    cur = conn.cursor()
-    serch_data = """select t1 from test where id = {table_id}""".format(table_id=id)
-    result = cur.execute(serch_data)
-    # 获取下一个查询结果集
-    record = cur.fetchone()
-    cur.close()  # 关闭数据库连接
-    return record
+from rules import MD5
+from sources import Sources, Sinks
+
 
 def getColumns(x):
     sql_list = []
@@ -52,64 +30,44 @@ def getColumns(x):
     print("---------------------->", sql)
     return sql
 
-def md5(col):
-    md5 = hashlib.md5()
-    md5.update(str(col).encode('utf-8'))
-    return md5.hexdigest()
-
 if __name__ == '__main__':
     # 拿到 列名 等
-    record = getRecordByIdResultT1(sys.argv[1])
+    record = Sources.getRecordByIdResultT1(sys.argv[1])
     col = json.loads(str(record)[2:-3]).get('col')
     sql = getColumns(str(record)[2:-3])
-    print(sql)
+    sink_method = json.loads(str(record)[2:-3]).get('sink_method')
 
     # spark 初始化
     spark = SparkSession.Builder().appName('sql').master('local').getOrCreate()
 
-    spark.udf.register('md5', md5, StringType())
-    print('=======>', output_file)
-    df = spark.read.format('csv').option('inferSchema', 'true').load(sys.argv[2]).toDF(*col)
-    df.count
+    spark.udf.register('md5', MD5.md5, StringType())
+    print('=======>', sys.argv[2])
+
+    df = Sources.readCsv(spark, sys.argv[2], col)
+
     t_table = df.createTempView('kino')
     sinkDF = spark.sql(sql)
     sinkDF.show()
 
-    '''
-        :param mode: specifies the behavior of the save operation when data already exists.
-        * ``append``: Append contents of this :class:`DataFrame` to existing data.
-        * ``overwrite``: Overwrite existing data.
-        * ``ignore``: Silently ignore this operation if data already exists.
-        * ``error`` or ``errorifexists`` (default case): Throw an exception if data already exists.
-        '''
-    sinkDF.write.mode("overwrite") \
-        .format("jdbc") \
-        .option("truncate", "true") \
-        .option("batchsize", 10000) \
-        .option("isolationLevel", "NONE") \
-        .option("driver", "org.mariadb.jdbc.Driver") \
-        .option("url", 'jdbc:mysql://hadoop1:3306/wanjia?useSSL=false') \
-        .option("user", 'root') \
-        .option("password", '123') \
-        .option("dbtable", "test1") \
-        .save()
-
-    # TODO 修改状态
-
-    # 落 ftp
-    # sinkDF.write.format("com.springml.spark.sftp")  \
-    #     .option("host", "192.168.31.45") \
-    #     .option("username", "raomin@9zdata.cn") \
-    #     .option("password", "9zdata123.") \
-    #     .option("fileType", "csv") \
-    #     .option("delimiter", ";") \
-    #     .save("ftp://192.168.31.45:21/wanjia/sample.csv")
-
-    # sinkDF.write.mode("overwrite").text("ftp://192.168.31.45/wanjia/sample.csv")
-
-    # sinkDF.write.format("parquet").mode("overwrite").save('hdfs://hadoop1:9000/wanjia')
-
+    if sink_method.lower() == 'hdfs':
+        # TODO 落 HDFS
+        Sinks.sinkHDFS(sinkDF, Constants.HDFS_PATH, "csv", Constants.SAVE_MODE_OVERWRITE)
+    elif sink_method.lower() == 'mysql':
+        # TODO 落 MySQL
+        Sinks.sinkMySql(sinkDF,
+                        mode=Constants.SAVE_MODE_OVERWRITE,
+                        driver=Constants.MY_MYSQL_DRIVER,
+                        url=Constants.MY_MYSQL_URL,
+                        user=Constants.MY_MYSQL_USER,
+                        password=Constants.MY_MYSQL_PASSWORD,
+                        table="test1")
+    elif sink_method.lower() == 'ftp':
+        print("落FTP")
+    else:
+        print("...")
 
+    # TODO 修改状态, 数据校验(读取-写出 数据量)
+    Sinks.updateMysqlStatus(i_status=1, i_readcount=df.count(), i_sinkcount=sinkDF.count(), i_id=1)
 
     # 关闭spark会话
     spark.stop()

spark/dependencies.sh

@@ -3,7 +3,6 @@ id=$1
 output_file=$2
 echo "传入的数据库id为: ${id}"
 echo "目标文件路径为: " ${output_file}
-#spark-submit --jars /usr/bigdata/spark-3.0.1-bin-hadoop3.2/jars/mariadb-java-client-2.1.2.jar --jars /usr/bigdata/spark-3.0.1-bin-hadoop3.2/jars/mysql-connector-java.jar dependencies.py ${id} ${output_file}
-#python3 dependencies.py --jars /usr/bigdata/spark-3.0.1-bin-hadoop3.2/jars/mariadb-java-client-2.1.2.jar  ${id} ${output_file}
 
-nohup spark-submit --jars /usr/bigdata/spark-3.0.1-bin-hadoop3.2/jars/mariadb-java-client-2.1.2.jar dependencies.py ${id} ${output_file}  > /root/test.log 2>&1 &
+# nohup spark-submit --jars /usr/bigdata/spark-3.0.1-bin-hadoop3.2/jars/mariadb-java-client-2.1.2.jar dependencies.py ${id} ${output_file}  > /root/test.log 2>&1 &
+spark-submit --jars /usr/bigdata/spark-3.0.1-bin-hadoop3.2/jars/mariadb-java-client-2.1.2.jar dependencies.py ${id} ${output_file}
\ No newline at end of file

spark/exception/MyErrorException.py

+class MyError(Exception):
+    def __init__(self, ErrorInfo):
+        super().__init__(self)
+        self.errorinfo = ErrorInfo
+
+    def __str__(self):
+        return self.errorinfo
+
+
+if __name__ == '__main__':
+    try:
+        raise MyError('零异常')
+    except MyError as e:
+        print("my exception currend:", e.errorinfo)
\ No newline at end of file

spark/rules/MD5.py

+import hashlib
+def md5(col):
+    md5 = hashlib.md5()
+    md5.update(str(col).encode('utf-8'))
+    return md5.hexdigest()
\ No newline at end of file

spark/sources/Sinks.py

+from common import Constants
+import exception.MyErrorException as ex
+
+# 写出到 MySQL
+from sources import Sources
+
+
+def sinkMySql(sinkDF, driver, url, user, password, table, mode=Constants.SAVE_MODE_OVERWRITE):
+    sinkDF.write.mode(mode) \
+        .format("jdbc") \
+        .option("truncate", "true") \
+        .option("batchsize", 10000) \
+        .option("isolationLevel", "NONE") \
+        .option("driver", driver) \
+        .option("url", url) \
+        .option("user", user) \
+        .option("password", password) \
+        .option("dbtable", table) \
+        .save()
+
+# 写出到FTP
+'''
+相关参数, 例如: 
+   host: 192.168.31.45
+   username: raomin@9zdata.cn
+   password: 9zdata123.
+   fileType: csv
+   file: ftp://192.168.31.45:21/wanjia/sample.csv
+'''
+def sinkFTP(sinkDF, host, user, password, filetype, file):
+    sinkDF.write.format("com.springml.spark.sftp")  \
+        .option("host", host) \
+        .option("username", user) \
+        .option("password", password) \
+        .option("fileType", filetype) \
+        .option("delimiter", ";") \
+        .save(file)
+
+# sink HDFS
+def sinkHDFS(sinkDF, path, format="parquet", mode=Constants.SAVE_MODE_OVERWRITE):
+    sinkDF\
+        .write\
+        .format(format)\
+        .mode(mode)\
+        .save(path)
+
+# 修改 MySQL 状态
+def updateMysqlStatus(i_status, i_readcount, i_sinkcount, i_id):
+    try:
+        conn = Sources.getMySqlConnect()
+        # 创建游标对象,用来给数据库发送sql语句
+        cur = conn.cursor()
+        serch_data = """update uptable set status={status}, readcount={readcount}, sinkcount={sinkcount} where id = {id}"""\
+            .format(status=i_status, readcount=i_readcount, sinkcount=i_sinkcount, id=i_id)
+        result = cur.execute(serch_data)
+    except ex.MyError as e:
+        print("update error", e.errorinfo)
+    finally:
+        cur.close()  # 关闭数据库连接
+        conn.close()
\ No newline at end of file

spark/sources/Sources.py

+import pymysql
+import exception.MyErrorException as ex
+
+def getMySqlConnect():
+    try:
+    # 连接数据库
+        conn = pymysql.connect(
+            host="hadoop1",  # 连接主机名,也可以用ip地址，例如127.0.0.1
+            user="root",  # 连接用户名
+            passwd="123",  # 用户密码
+            db="wanjia",  # 要连接的数据库名
+            charset="utf8",  # 指定编码格式
+            autocommit=True,  # 如果插入数据，， 是否自动提交? 和conn.commit()功能一致。
+        )
+    except ex.MyError as e:
+        print("connection error", e.errorinfo)
+    return conn
+
+
+def getRecordByIdResultT1(id):
+    conn = getMySqlConnect()
+    # 创建游标对象,用来给数据库发送sql语句
+    try:
+        cur = conn.cursor()
+        serch_data = """select t1 from test where id = {table_id}""".format(table_id=id)
+        result = cur.execute(serch_data)
+        # 获取下一个查询结果集
+        record = cur.fetchone()
+    except ex.MyError as e:
+        print("executor failed", e.errorinfo)
+    finally:
+        cur.close()  # 关闭数据库连接
+        conn.close()
+    return record
+
+def readCsv(spark, path, col):
+    df = spark.read.format('csv').option('inferSchema', 'true').load(path).toDF(*col)
+    return df

spark/unzip.py

 #!/usr/local/bin/python
-
 import sys
 import os
 import shutil
 import zipfile
-
+import exception.MyErrorException as ex
 pyName = sys.argv[0]   #sys.argv[0] 类似于shell中的$0, 但不是脚本名称，而是脚本的路径
 zipPath = sys.argv[1]    #sys.argv[1] 表示传入的第一个参数
 inputPath = sys.argv[2]    #sys.argv[2] 表示传入的第二个参数
 outputPath = sys.argv[3]
-
+# os.system("hdfs dfs -put /srcPath /dstPath")
 def get_file(srcPath, dstPath):
+    try:
+        if not os.path.exists(srcPath):
+            print("srcPath not exist")
+        else:
             res = []
             for root, dirs, files in os.walk(srcPath, True):
                 for fileName in files:
                     name, suf = os.path.splitext(fileName)
                     if fileName.endswith('.csv'):
                         shutil.copy(os.path.join(root, fileName), dstPath)
+    except ex.MyError as e:
+        print("失败", e.errorinfo)
 
 def unzip_file(zip_file_name, destination_path):
+    try:
         archive = zipfile.ZipFile(zip_file_name, mode='r')
         for file in archive.namelist():
             archive.extract(file, destination_path)
+    except ex.MyError as e:
+        print("解压失败", e.errorinfo)
+        sys.exit()
+
+
 
 if __name__ == '__main__':
     print('解压、复制中...')

spark/unzip.sh

@@ -2,9 +2,7 @@
 echo -e "\033[34m==========文件解压、复制开始\033[0m=========="
 python3 unzip.py /root/wanjia/files/zip_file/20201102/20201102.zip /root/wanjia/files/input_file/20201102 /root/wanjia/files/output_file/20201102
 echo -e "\033[34m==========文件解压、复制结束\033[0m=========="
-
 echo ""
-
 echo -e "\033[34m==========将id写入环境变量\033[0m============"
 # echo '{"id": 1}' >> ${JOB_OUTPUT_PROP_FILE}
 echo '{"id": 1, "output_file": "/root/wanjia/files/output_file/20201102"}' >> ${JOB_OUTPUT_PROP_FILE}