我在rbdms中有一个表列表(跨不同的类别),我想提取并保存在hive中,并且我想以这样一种方式进行参数化,以便能够将类别名称附加到hive中的输出位置。例如,我有一个类别“employee”,我希望能够以“hive\u db.employee\u some\u other\u random\u name”的格式保存rdbms中提取的表
我有如下代码
val category = "employee"
val tableList = List("schema.table_1", "schema.table_2", "schema.table_3")
val tableMap = Map("schema.table_1" -> "table_1",
"schema.table_2" -> "table_2",
"schema.table_3" -> "table_3")
val queryMap = Map("table_1" -> (select * from table_1) tble,
"table_2" -> (select * from table_2) tble,
"table_3" -> (select * from table_3) tble)
val tableBucketMap = Map("table_1" -> "bucketBy(80,\"EMPLOY_ID\",\"EMPLOYE_ST\").sortBy(\"EMPLOY_ST\").format(\"parquet\")",
"table_2" -> "bucketBy(80, \"EMPLOY_ID\").sortBy(\"EMPLOY_ID\").format(\"parquet\")",
"table_3" -> "bucketBy(80, \"EMPLOY_ID\", \"SAL_ID\", \"DEPTS_ID\").sortBy(\"EMPLOY_ID\").format(\"parquet\")")
for (table <- tableList){
val tableName = tableMap(table)
val print_start = "STARTING THE EXTRACTION PROCESSING FOR TABLE: %s"
val print_statement = print_start.format(tableName)
println(print_statement)
val extract_query = queryMap(table)
val query_statement_non = "Query to extract table %s is: "
val query_statement = query_statement_non.format(tableName)
println(query_statement + extract_query)
val extracted_table = spark.read.format("jdbc")
.option("url", jdbcURL)
.option("driver", driver_type)
.option("dbtable", extract_query)
.option("user", username)
.option("password", password)
.option("fetchsize", "20000")
.option("queryTimeout", "0")
.load()
extracted_table.show(5, false)
//saving extracted table in hive
val tableBucket = tableBucketMap(table)
val output_loc = "hive_db.%s_table_extracted_for_%s"
val hive_location = output_loc.format(category, tableName)
println(hive_location)
val saving_table = "%s.write.%s.saveAsTable(\"%s\")"
saving_table.format(extracted_table, tableBucket, hive_location)
println(saving_table.format(extracted_table, tableBucket, hive_location))
val print_end = "COMPLETED EXTRACTION PROCESS FOR TABLE: %s"
val print_end_statement = print_end.format(tableName)
println(print_end_statement)
我有以下第一个表格的结果。同样的结果也适用于其他表格。。
STARTING THE EXTRACTION PROCESSING FOR TABLE: table_1
Query to extract table table_1 is: (select * from table_1) tble
+---------+--------------------+
|EMPLOY_ID|EMPLOYE_NM |
+---------+--------------------+
|1 |WELLINGTON |
|2 |SMITH |
|3 |CURLEY |
|4 |PENDRAGON |
|5 |KEESLER |
+---------+--------------------+
only showing top 5 rows
hive_db.employee_table_extracted_for_table_1
[EMPLOY_ID: int, EMPLOYE_NM: string].write.bucketBy(80, "EMPLOY_ID", "EMPLOYE_NO").sortBy("EMPLOY_ID").format("parquet").saveAsTable("hive_db.employee_table_extracted_for_table_1")
COMPLETED EXTRACTION PROCESS FOR TABLE: table_1
它没有将提取的Dataframe写入配置单元,而是打印列名
[EMPLOY_ID: int, EMPLOYE_NM: String].write............saveAsTable("hive_db.employee_table_extracted_for_table_1")
如何将df写入hive表?
1条答案
按热度按时间tpgth1q71#
你能试试这个方法吗,像这样改变你的桶图(我已经为t1做了,请为t2和t3做同样的事情),
并更换
df.bucketBy()
有足够的论据(numBuckets: Int, colName: String, colNames: String*)
```val stringArr=tableBucket.split(",")
val numBuckets=stringArr(0).toInt
val colName=stringArr(1)
[EMPLOY_ID: int, EMPLOYE_NM: String].write............saveAsTable("hive_db.employee_table_extracted_for_table_1")