Iceberg unit tests, support Iceberg + nonhive catalogs, Iceberg Kryo Serializer #993
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -239,9 +239,15 @@ case object Iceberg extends Format { | |
| override def partitions(tableName: String, partitionColumns: Seq[String])(implicit | ||
| sparkSession: SparkSession): Seq[Map[String, String]] = { | ||
| sparkSession.sqlContext | ||
| .sql(s"SELECT partition FROM $tableName" ++ ".partitions") | ||
|
There was a problem hiding this comment. ooc does this work for regular hive tables? There was a problem hiding this comment. This is for iceberg, Hive support is here There was a problem hiding this comment. it should work for hive tables, and the internal target I'm hitting are more or less "regular hive tables". Iceberg abstracts itself from the catalog implementation, so as long as your iceberg has an interface to your catalog implementation, it will work. |
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| .collect() | ||
| .map { row => | ||
| val partitionStruct = row.getStruct(0) | ||
| partitionStruct.schema.fieldNames.zipWithIndex.map { | ||
| case (fieldName, idx) => | ||
| fieldName -> partitionStruct.get(idx).toString | ||
| }.toMap | ||
| } | ||
| } | ||
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| private def getIcebergPartitions(tableName: String, | ||
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@@ -395,7 +401,14 @@ case class TableUtils(sparkSession: SparkSession) { | |
| rdd | ||
| } | ||
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| def tableExists(tableName: String): Boolean = { | ||
| try { | ||
| sparkSession.sql(s"DESCRIBE TABLE $tableName") | ||
| true | ||
| } catch { | ||
| case _: AnalysisException => false | ||
| } | ||
| } | ||
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| def loadEntireTable(tableName: String): DataFrame = sparkSession.table(tableName) | ||
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@@ -973,17 +986,38 @@ case class TableUtils(sparkSession: SparkSession) { | |
| partitions: Seq[String], | ||
| partitionColumn: String = partitionColumn, | ||
| subPartitionFilters: Map[String, String] = Map.empty): Unit = { | ||
| // TODO this is using datasource v1 semantics, which won't be compatible with non-hive catalogs | ||
| // notably, the unit test iceberg integration uses hadoop because of | ||
| // https://github.com/apache/iceberg/issues/7847 | ||
| if (partitions.nonEmpty && tableExists(tableName)) { | ||
| val dropSql = tableFormatProvider.readFormat(tableName) match { | ||
| // really this is Dsv1 vs Dsv2, not hive vs iceberg, | ||
| // but we break this way since only Iceberg is migrated to Dsv2 | ||
| case Iceberg => | ||
| // Build WHERE clause: (ds='2024-05-01' OR ds='2024-05-02') [AND k='v' AND …] | ||
| val mainPred = partitions | ||
| .map(p => s"$partitionColumn='${p}'") | ||
| .mkString("(", " OR ", ")") | ||
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| val extraPred = subPartitionFilters | ||
| .map { case (k, v) => s"$k='${v}'" } | ||
| .mkString(" AND ") | ||
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| val where = Seq(mainPred, extraPred).filter(_.nonEmpty).mkString(" AND ") | ||
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| s"DELETE FROM $tableName WHERE $where" | ||
| case _ => | ||
| val partitionSpecs = partitions | ||
| .map { partition => | ||
| val mainSpec = s"$partitionColumn='$partition'" | ||
| val specs = mainSpec +: subPartitionFilters.map { | ||
| case (key, value) => s"${key}='${value}'" | ||
| }.toSeq | ||
| specs.mkString("PARTITION (", ",", ")") | ||
| } | ||
| .mkString(",") | ||
| s"ALTER TABLE $tableName DROP IF EXISTS $partitionSpecs" | ||
| } | ||
| sql(dropSql) | ||
| } else { | ||
| logger.info(s"$tableName doesn't exist, please double check before drop partitions") | ||
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how is working with metals relative to intellij? does the debugger work as well?
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It's really good actually. The debugged worked out of the box, I found it comparable to IntelliJ overall.
I'd recommend it to anyone who has remote dev boxes since VSCode's integration is far better in my experience. All the tests run a lot faster and I got in way more dev cycles. I probably would only recommend over IntelliJ with a dev box though.