USER
Change field value hardcoding to parametrized fields : "First, let’s clean up the code by replacing non-ASCII quotes and special characters, updating imports, and adding necessary import statements:
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.functions;
import static org.apache.spark.sql.functions.*;
public class SCDType2Example {
public static void main(String[] args) {
SparkSession spark = SparkSession
.builder()
.appName(“SCDDevice2Example”)
.master(“local”)
.getOrCreate();
Dataset<Row> oldData = spark.read().parquet(“path/to/oldData”);
Dataset<Row> newData = spark.read().parquet(“path/to/newData”);
// Repartition the data
oldData = oldData.repartition(“id”);
newData = newData.repartition(“id”);
String primaryKey = “id”;
String[] nonKeyColumns = {“name”, “age”, “city”}; // Parametrizable columns
String hashColumn = “hash”;
oldData = createHash(oldData, nonKeyColumns, hashColumn);
newData = createHash(newData, nonKeyColumns, hashColumn);
Dataset<Row> joinedData = oldData.join(
broadcast(newData),
oldData.col(primaryKey).equalTo(newData.col(primaryKey)),
“fullouter” // Changed
);
Dataset<Row> result = joinedData
.withColumn(“hash_1”, coalesce(oldData.col(“hash”), lit(“”)))
.withColumn(“hash_2”, coalesce(newData.col(“hash”), lit(“”)))
.withColumn(“date”, current_date())
.select(
when(oldData.col(primaryKey).isNull(), newData.col(primaryKey)).otherwise(oldData.col(primaryKey)).alias(primaryKey),
when(oldData.col(“hash”).equalTo(newData.col(“hash”)), oldData.col(“name”)).otherwise(newData.col(“name”)).alias(“name”),
when(oldData.col(“hash”).equalTo(newData.col(“hash”)), oldValue(“age”)).otherwise(newData.col(“age”)).alias(“age”),
when(oldData.col(“hash”).equalTo(newData.col(“hash”)), oldData.col(“city”)).otherwise(newData.col(“city”)).alias(“city”),
when(oldData.col(“hash”).equalTo(newData.col(“hash”)), oldData.col(“start_date”)).otherwise(oldData.col(“start_date”)).alias(“start_date”),
when(oldData.col(“hash”).notEqual(newData.col(“hash”)), current_date()).otherwise(oldData.col(“end_date”)).alias(“end_date”),
when(oldData.col(“hash”).isNull(), lit(true)).otherwise(oldData.col(“hash”).equalTo(newData.col(“hash”))).alias(“current_flag”),
when(newData.col(“hash”).isNull(), lit(false)).otherwise(oldData.col(“hash”).notEqual(newData.col(“hash”))).alias(“update_flag”)
);
result.write().parquet(“path/to/output”);
}
private static Dataset<Row> createHash(Dataset<Row> data, String[] nonKeyColumns, String hashColumn) {
Dataset<Row> result = data;
StringBuilder concatString = new StringBuilder();
for (String column : nonKeyColumns) {
concatString.append(“cast(”).append(column).append(" as string),“);
}
String concatColumns = concatString.toString();
if (concatColumns.endsWith(”,“)) {
concatColumns = concatColumns.substring(0, concatColumns.length() - 1);
}
return result.withColumn(hashColumn, sha2(functions.concat_ws(”", functions.expr(concatColumns)), 256));
}
}
"ASSISTANT
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.functions;
import static org.apache.spark.sql.functions.*;
public class SCDType2Example {
public static void main(String[] args) {
SparkSession spark = SparkSession
.builder()
.appName("SCDDevice2Example")
.master("local")
.getOrCreate();
Dataset<Row> oldData = spark.read().parquet("path/to/oldData");
Dataset<Row> newData = spark.read().parquet("path/to/newData");
// Repartition the data
oldData = oldData.repartition("id");
newData = newData.repartition("id");
String primaryKey = "id";
String[] nonKeyColumns = {"name", "age", "city"}; // Parametrizable columns
String hashColumn = "hash";
oldData = createHash(oldData, nonKeyColumns, hashColumn);
newData = createHash(newData, nonKeyColumns, hashColumn);
Dataset<Row> joinedData = oldData.join(
broadcast(newData),
oldData.col(primaryKey).equalTo(newData.col(primaryKey)),
"fullouter"
);
Dataset<Row> result = joinedData
.withColumn("hash_1", coalesce(oldData.col("hash"), lit("")))
.withColumn("hash_2", coalesce(newData.col("hash"), lit("")))
.withColumn("date", current_date())
.select(
when(oldData.col(primaryKey).isNull(), newData.col(primaryKey)).otherwise(oldData.col(primaryKey)).alias(primaryKey),
when(oldData.col("hash").equalTo(newData.col("hash")), oldData.col("name")).otherwise(newData.col("name")).alias("name"),
when(oldData.col("hash").equalTo(newData.col("hash")), oldValue("age")).otherwise(newData.col("age")).alias("age"),
when(oldData.col("hash").equalTo(newData.col("hash")), oldData.col("city")).otherwise(newData.col("city")).alias("city"),
when(oldData.col("hash").equalTo(newData.col("hash")), oldData.col("start_date")).otherwise(oldData.col("start_date")).alias("start_date"),
when(oldData.col("hash").notEqual(newData.col("hash")), current_date()).otherwise(oldData.col("end_date")).alias("end_date"),
when(oldData.col("hash").isNull(), lit(true)).otherwise(oldData.col("hash").equalTo(newData.col("hash"))).alias("current_flag"),
when(newData.col("hash").isNull(), lit(false)).otherwise(oldData.col("hash").notEqual(newData.col("hash"))).alias("update_flag")
);
result.write().parquet("path/to/output");
}
private static Dataset<Row> createHash(Dataset<Row> data, String[] nonKeyColumns, String hashColumn) {
Dataset<Row> result = data;
StringBuilder concatString = new StringBuilder();
for (String column : nonKeyColumns) {
concatString.append("cast(").append(column).append(" as string),");
}
String concatColumns = concatString.toString();
if (concatColumns.endsWith(",")) {
concatColumns = concatColumns.substring(0, concatColumns.length() - 1);
}
return result.withColumn(hashColumn, sha2(functions.concat_ws("", functions.expr(concatColumns)), 256));
}
}