xiarixiaoyao commented on issue #5452:
URL: https://github.com/apache/hudi/issues/5452#issuecomment-1240122505
@santoshsb you need use schema evolution and
hoodie.datasource.write.reconcile.schema, see the follow codes
```
def perf(spark: SparkSession) = {
import org.apache.spark.sql.SaveMode
import org.apache.spark.sql.functions._
import org.apache.hudi.DataSourceWriteOptions
import org.apache.hudi.DataSourceReadOptions
import org.apache.hudi.config.HoodieWriteConfig
import org.apache.hudi.hive.MultiPartKeysValueExtractor
//Define a Patient FHIR resource, for simplicity have deleted most of
the elements and retained a few
val orgString =
"""{"resourceType":"Patient","id":"beca9a29-49bb-40e4-adff-4dbb4d664972","lastUpdated":"2022-02-14T15:18:18.90836+05:30","source":"4a0701fe-5c3b-482b-895d-875fcbd2148a","name":[{"use":"official","family":"Keeling57","given":["Serina556"],"prefix":["Ms."]}]}"""
val sqlContext = spark.sqlContext
import sqlContext.implicits._
val orgStringDf = spark.read.json(Seq(orgString).toDS)
//Specify common DataSourceWriteOptions in the single hudiOptions
variable
val hudiOptions = Map[String,String](
HoodieWriteConfig.TABLE_NAME -> "patient_hudi",
DataSourceWriteOptions.TABLE_TYPE_OPT_KEY -> "COPY_ON_WRITE",
DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY -> "id",
DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY -> "source",
DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY -> "lastUpdated",
DataSourceWriteOptions.HIVE_STYLE_PARTITIONING_OPT_KEY -> "true")
//Write the orgStringDf to a Hudi table
orgStringDf.write
.format("org.apache.hudi")
.option(DataSourceWriteOptions.OPERATION_OPT_KEY,
DataSourceWriteOptions.INSERT_OPERATION_OPT_VAL)
.options(hudiOptions)
.mode(SaveMode.Overwrite)
.save("/work/data/updateTst/hudi/json_schema_tst")
//Read the Hudi table
val patienthudi =
spark.read.format("hudi").load("/work/data/updateTst/hudi/json_schema_tst")
//Printschema
patienthudi.printSchema
//Update: Based on our usecase add a new patient resource, this resource
might contain new columns and might not have existing columns (normal use case
with FHIR data)
val updatedString =
"""{"resourceType":"Patient","id":"beca9a29-49bb-40e4-adff-4dbb4d664972","lastUpdated":"2022-02-14T15:18:18.90836+05:30","source":"4a0701fe-5c3b-482b-895d-875fcbd2148a","name":[{"use":"official","family":"Keeling57","given":["Serina556"]}]}"""
//Convert the new resource string into DF
val updatedStringDf = spark.read.json(Seq(updatedString).toDS)
//Check the schema of the new resource that is being added
updatedStringDf.printSchema
//Upsert the new resource
spark.sql("set hoodie.schema.on.read.enable=true")
updatedStringDf.write
.format("org.apache.hudi")
.options(hudiOptions)
.option(DataSourceWriteOptions.OPERATION_OPT_KEY,
DataSourceWriteOptions.UPSERT_OPERATION_OPT_VAL)
.option(DataSourceWriteOptions.PAYLOAD_CLASS_OPT_KEY,
"org.apache.hudi.common.model.EmptyHoodieRecordPayload")
.option("hoodie.datasource.write.reconcile.schema", "true")
.mode(SaveMode.Append)
.save("/work/data/updateTst/hudi/json_schema_tst")
//Read the Hudi table
val patienthudiUpdated =
spark.read.format("hudi").load("/work/data/updateTst/hudi/json_schema_tst")
//Print the schema after adding the new record
patienthudiUpdated.printSchema
}
```
patienthudiUpdated.schema:
|-- _hoodie_commit_time: string (nullable = true)
|-- _hoodie_commit_seqno: string (nullable = true)
|-- _hoodie_record_key: string (nullable = true)
|-- _hoodie_partition_path: string (nullable = true)
|-- _hoodie_file_name: string (nullable = true)
|-- id: string (nullable = true)
|-- lastUpdated: string (nullable = true)
|-- name: array (nullable = true)
| |-- element: struct (containsNull = true)
| | |-- family: string (nullable = true)
| | |-- given: array (nullable = true)
| | | |-- element: string (containsNull = true)
| | |-- prefix: array (nullable = true)
| | | |-- element: string (containsNull = true)
| | |-- use: string (nullable = true)
|-- resourceType: string (nullable = true)
|-- source: string (nullable = true)
i think it should be ok , thanks
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