Question

我有一个Avro模式文件，我需要通过pyspark在Databricks中创建一个表。我不需要加载数据，只想创建表。最简单的方法是加载JSON字符串，并从"name"数组中提取"type"和fields。然后生成CREATE SQL查询。我想知道是否有任何编程方法可以使用任何API进行此操作。示例架构-

{
  "type" : "record",
  "name" : "kylosample",
  "doc" : "Schema generated by Kite",
  "fields" : [ {
    "name" : "registration_dttm",
    "type" : "string",
    "doc" : "Type inferred from '2016-02-03T07:55:29Z'"
  }, {
    "name" : "id",
    "type" : "long",
    "doc" : "Type inferred from '1'"
  }, {
    "name" : "first_name",
    "type" : "string",
    "doc" : "Type inferred from 'Amanda'"
  }, {
    "name" : "last_name",
    "type" : "string",
    "doc" : "Type inferred from 'Jordan'"
  }, {
    "name" : "email",
    "type" : "string",
    "doc" : "Type inferred from 'ajordan0@com.com'"
  }, {
    "name" : "gender",
    "type" : "string",
    "doc" : "Type inferred from 'Female'"
  }, {
    "name" : "ip_address",
    "type" : "string",
    "doc" : "Type inferred from '1.197.201.2'"
  }, {
    "name" : "cc",
    "type" : [ "null", "long" ],
    "doc" : "Type inferred from '6759521864920116'",
    "default" : null
  }, {
    "name" : "country",
    "type" : "string",
    "doc" : "Type inferred from 'Indonesia'"
  }, {
    "name" : "birthdate",
    "type" : "string",
    "doc" : "Type inferred from '3/8/1971'"
  }, {
    "name" : "salary",
    "type" : [ "null", "double" ],
    "doc" : "Type inferred from '49756.53'",
    "default" : null
  }, {
    "name" : "title",
    "type" : "string",
    "doc" : "Type inferred from 'Internal Auditor'"
  }, {
    "name" : "comments",
    "type" : "string",
    "doc" : "Type inferred from '1E+02'"
  } ]
}

Answer 1

这似乎还不能通过Python API来使用。。。这是我过去通过Spark SQL创建一个指向您导出的.avsc的外部表的方式，因为您只想创建一个表并不加载任何数据...例如：

spark.sql("""
create external table db.table_name
STORED AS AVRO
LOCATION 'PATH/WHERE/DATA/WILL/BE/STORED'
TBLPROPERTIES('avro.schema.url'='PATH/TO/SCHEMA.avsc')
""")

Spark 2.4中的本机Scala API似乎现在已提供.avsc阅读器……由于您使用的是Databricks，因此可以像%scala or %python or %sql这样的笔记本中更改内核……Scala示例：

import org.apache.avro.Schema

val schema = new Schema.Parser().parse(new File("user.avsc"))

spark
  .read
  .format("avro")
  .option("avroSchema", schema.toString)
  .load("/tmp/episodes.avro")
  .show()

Spark 2.4 Avro集成的参考文档=>

https://spark.apache.org/docs/latest/sql-data-sources-avro.html#configuration

https://databricks.com/blog/2018/11/30/apache-avro-as-a-built-in-data-source-in-apache-spark-2-4.html

如何从avro模式（.avsc）创建表？

1 个答案: