我正在搜索与功能 from_unixtime（bigint unixtime）等效的功能，该功能存在于Spark-SQL和Flink-SQL中。
我的目标是转换这种格式：1439799094
转换为这种格式：2015-05-18 05:43:37
答案 0 :(得分：1)
只需使用UDF！
https://ci.apache.org/projects/flink/flink-docs-stable/dev/table/udfs.html
样品用量
add_filter( 'woocommerce_default_address_fields' ,'custom_override_default_address_fields' );
$answer = $_POST['payment_method'];
if ( $answer == "cppec_paypal" ) {
function custom_override_default_address_fields( $address_fields ) {
$address_fields['address_1']['required'] = false;
return $address_fields;
}
...
test.csv creation_date|key
1535816823|1
1536392928|2
1536272308|3
EpochTimeConverter.scala import java.time.format.DateTimeFormatter
import java.time.{Instant, LocalDateTime, ZoneId}
import org.apache.flink.table.functions.ScalarFunction
class EpochTimeConverter extends ScalarFunction {
def eval(epochTime: Int): String = {
// For performance, you may cache `DateTimeFormatter` in real life
val timePattern = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss")
timePattern.format(LocalDateTime.ofInstant(Instant.ofEpochSecond(epochTime), ZoneId.systemDefault()))
}
}
UdfExample.scala如果运行import org.apache.flink.api.scala.{ExecutionEnvironment, _}
import org.apache.flink.table.api.scala._
import org.apache.flink.table.api.{TableEnvironment, Types}
import org.apache.flink.table.sources.CsvTableSource
import org.apache.flink.types.Row
object UdfExample {
def main(args: Array[String]): Unit = {
val env = ExecutionEnvironment.getExecutionEnvironment
val tableEnv = TableEnvironment.getTableEnvironment(env)
val csvData = CsvTableSource
.builder()
.path("test.csv")
.ignoreFirstLine()
.fieldDelimiter("|")
.field("creation_date", Types.INT)
.field("key", Types.INT)
.build()
tableEnv.registerTableSource("temp_table", csvData)
println("Without udf:")
tableEnv.sqlQuery("SELECT creation_date, key FROM temp_table").toDataSet[Row].print()
tableEnv.registerFunction("from_unixtime", new EpochTimeConverter())
println()
println("With udf:")
tableEnv.sqlQuery("select from_unixtime(creation_date),key from temp_table").toDataSet[Row].print()
}
}
，它将产生类似以下的输出：
UdfExample.scala答案 1 :(得分：-1)
我认为您正在寻找DATE_FORMAT(timestamp, '%Y-%m-%d %H:%i:%s')。
有关更多信息，请参见built-in functions和date format specifiers上的文档。