datax之json格式
司马念
1、datax直接从hdfs数据表上读取数据，写入到sqlserver
{
"job": {
"content": [
{
"reader": {
"name": "hdfsreader",
"parameter": {
"defaultFS": "hdfs://cnprod1ha",
"fieldDelimiter": ",",
"fileType": "orc",
"path": "/user/hive/userdbs/svccnahahs.db/dwd_dc_appointment_data_d/",
"filename":"tmp1",
"hadoopConfig":{
"dfs.nameservices": "cnprod1ha",
"dfs.ha.namenodes.cnprod1ha": "namenode1,namenode2",
"dfs.namenode.rpc-address.cnprod1ha.namenode1": "oser406433.cn.wal-mart.com:8020",
"dfs.namenode.rpc-address.cnprod1ha.namenode2": "oser406435.cn.wal-mart.com:8020",
"dfs.client.failover.proxy.provider.testDfs": "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
},
"column": [
{
"index": 0,
"type": "string"
},
{
"index": 1,
"type": "string"
},
{
"index": 2,
"type": "string"
}
],
"fieldDelimiter": ","
}
},
"writer": {
"name": "sqlserverwriter",
"parameter": {
"username": "datalakereportrw",
"password": "Dat@r1P2w",
"column": [
"dc"
,"appointment_nbr"
,"scheduled_date"
,"scheduled_time"
],
"connection": [
{
"table": [
"dwd_dc_appointment_data_d"
],
"jdbcUrl": "jdbc:sqlserver://10.88.133.71:1433;DatabaseName=DataLakeReport"
}
]
}
}
}
],
"setting": {
"speed": {
"channel": "3"
}
}
}
}
2、datax从hdfs读取数据，写入到clickhouse
{
"job": {
"setting": {
"speed": {
"channel": 2
}
},
"content": [
{ "reader": {
"name": "hdfsreader",
"parameter": {
"defaultFS": "hdfs://cnprod1ha",
"fileType": "orc",
"path": "/tmp/sqoop/export/hadoop服务器名/rpt/dim_calendar/*",
"hadoopConfig":{
"dfs.nameservices": "cnprod1ha",
"dfs.ha.namenodes.cnprod1ha": "namenode1,namenode2",
"dfs.namenode.rpc-address.cnprod1ha.namenode1": "oser406433.cn.wal-mart.com:8020",
"dfs.namenode.rpc-address.cnprod1ha.namenode2": "oser406435.cn.wal-mart.com:8020",
"dfs.client.failover.proxy.provider.testDfs": "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
},
"column": [
{
"index": 0,
"type": "string"
},
{
"index": 1,
"type": "string"
},
{
"index": 2,
"type": "string"
},
{
"index": 3,
"type": "string"
},
{
"index": 4,
"type": "string"
},
{
"index": 5,
"type": "string"
}
],
"fieldDelimiter": "|"
}
},
"writer": {
"name": "rdbmswriter",
"parameter": {
"connection": [
{
"jdbcUrl": "jdbc:clickhouse://服务器名:8123/库",
"table": [
"dim_calendar"
]
}
],
"username": "username",
"password": "password",
"table": "dim_calendar",
"column": [
"*"
],
"preSql": [
"alter table dim_calendar on cluster cluster_rpt delete where event_date between ${start_date} and ${end_date}"
]
}
}
}
]
}
}
上述json中变量，可在shell中进行变量替换，shell如下
#! /bin/bash -x
source ~/.bash_profile
declare -r CURR_DIR=$(cd `dirname $0`;pwd)
JOB_NAME=`basename $0 .sh`
start_date=${1:-`date -d '-15 day' '+%Y-%m-%d'`} # T+30
end_date=${2:-`date -d '-1 day' '+%Y-%m-%d'`} # T+1
DB_NAME=${3:-"cn_ominchan_sales_dl_tables"}
QUEUE_NAME=${4:-"smartops"}```
# to HDFS
hive --hivevar start_date="${start_date}" \
--hivevar end_date="${end_date}" \
-f ${CURR_DIR}/app_sales_full_channel_m_export.sql
#数据同步到clickhouse
tmpfile4=`mktemp -t sql_XXXX.sql`
cat ${CURR_DIR}/app_sales_full_channel_m.json > $tmpfile4
sed -i "s/__start_date__/${start_date}/g ; s/__end_date__/${end_date}/g" $tmpfile4
datax $tmpfile4
3、datax从sqlserver读取数据写入到sqlserver
{
"job": {
"setting": {
"speed": {
"channel": 5
} },
"content": [
{
"reader": {
"name": "sqlserverreader",
"parameter": {
"username": "xx",
"password": "xx",
"where": "",
"connection": [
{
"querySql": [
"select * from dbo.test01;"
],
"jdbcUrl": [
"jdbc:sqlserver://192.168.130.122:1433;DatabaseName=HX"
]
}
]
}
},
"writer": {
"name": "sqlserverwriter",
"parameter": {
"username": "xx",
"password": "xx",
"column": [
"id",
"ids",
"age"
],
"connection": [
{
"table": [
"table_name"
],
"jdbcUrl": "jdbc:sqlserver://192.168.130.122:1433;DatabaseName=HXS"
}
]
}
}
}
]
}
}
4、datax从sqlserver同步数据到hive
{
"job": {
"content": [
{
"reader": {
"name": "sqlserverreader", #sqlserver读取器
"parameter": {
"username": "your_user_name", #用户名
"password": "your_password", #密码
"connection": [
{
"querySql": [
"SELECT order_id,store_name from ${database_name}.dbo.${table_name} where date between '' and '' "
],
"jdbcUrl": ["jdbc:sqlserver://ip:1433"] #地址和端口，默认 1433
}
]
}
},
"writer": {
"name": "hdfswriter", #hdfs写入器
"parameter": {
"defaultFS": "hdfs://cnprod1ha", #hdfs上的地址
"fileType": "orc", #导出的文件存储格式
"path": "/tmp/sqoop/export/vn0c43l/lcm/${your_dest_dir}", #你要导出的目标路径，提前创建好
"fileName": "${sams}", #导出的文件前缀名
"hadoopConfig":{ #hdfs配置，就按照这个写就行
"dfs.nameservices": "cnprod1ha",
"dfs.ha.namenodes.cnprod1ha": "namenode1,namenode2",
"dfs.namenode.rpc-address.cnprod1ha.namenode1": "oser406433.cn.wal-mart.com:8020",
"dfs.namenode.rpc-address.cnprod1ha.namenode2": "oser406435.cn.wal-mart.com:8020",
"dfs.client.failover.proxy.provider.testDfs": "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
},
"column": [
{
"name": "order_id", #和你上面查询的一致，还有类型
"type": "VARCHAR"
},
{
"name": "store_name",
"type": "VARCHAR"
}
],
"writeMode": "append", #导出模式，这里是追加
"fieldDelimiter": "|" #导出的文件中字段的分隔符
}
}
}
],
"setting": {
"speed": {
"channel": "3"
}
}
}
}
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