Add support for reading parquet file thanks to arrow-dataset #576

Author: fb64

dataframe-arrow/build.gradle.kts

@@ -13,6 +13,7 @@ dependencies {
     implementation(libs.arrow.vector)
     implementation(libs.arrow.format)
     implementation(libs.arrow.memory)
+    implementation(libs.arrow.dataset)
     implementation(libs.commonsCompress)
     implementation(libs.kotlin.reflect)
     implementation(libs.kotlin.datetimeJvm)

dataframe-arrow/src/main/kotlin/org/jetbrains/kotlinx/dataframe/io/arrowReading.kt

@@ -1,5 +1,6 @@
 package org.jetbrains.kotlinx.dataframe.io
 
+import org.apache.arrow.dataset.file.FileFormat
 import org.apache.arrow.memory.RootAllocator
 import org.apache.arrow.vector.ipc.ArrowReader
 import org.apache.commons.compress.utils.SeekableInMemoryByteChannel
@@ -186,3 +187,11 @@ public fun DataFrame.Companion.readArrow(
 public fun ArrowReader.toDataFrame(
     nullability: NullabilityOptions = NullabilityOptions.Infer
 ): AnyFrame = DataFrame.Companion.readArrowImpl(this, nullability)
+
+/**
+ * Read [Parquet](https://parquet.apache.org/) data from existing [url] by using [Arrow Dataset](https://arrow.apache.org/docs/java/dataset.html)
+ */
+public fun DataFrame.Companion.readParquet(
+    url: URL,
+    nullability: NullabilityOptions = NullabilityOptions.Infer
+): AnyFrame = readArrowDataset(url.toString(), FileFormat.PARQUET, nullability)

dataframe-arrow/src/main/kotlin/org/jetbrains/kotlinx/dataframe/io/arrowReadingImpl.kt

@@ -1,5 +1,10 @@
 package org.jetbrains.kotlinx.dataframe.io
 
+import org.apache.arrow.dataset.file.FileFormat
+import org.apache.arrow.dataset.file.FileSystemDatasetFactory
+import org.apache.arrow.dataset.jni.DirectReservationListener
+import org.apache.arrow.dataset.jni.NativeMemoryPool
+import org.apache.arrow.dataset.scanner.ScanOptions
 import org.apache.arrow.memory.RootAllocator
 import org.apache.arrow.vector.BigIntVector
 import org.apache.arrow.vector.BitVector
@@ -296,7 +301,7 @@ internal fun DataFrame.Companion.readArrowImpl(
                         add(df)
                     }
                 }
-                is ArrowStreamReader -> {
+                else -> {
                     val root = reader.vectorSchemaRoot
                     val schema = root.schema
                     while (reader.loadNextBatch()) {
@@ -309,3 +314,27 @@ internal fun DataFrame.Companion.readArrowImpl(
         return flattened.concatKeepingSchema()
     }
 }
+
+internal fun DataFrame.Companion.readArrowDataset(
+    fileUri: String,
+    fileFormat: FileFormat,
+    nullability: NullabilityOptions = NullabilityOptions.Infer,
+): AnyFrame {
+    val scanOptions = ScanOptions(32768)
+    RootAllocator().use { allocator ->
+        FileSystemDatasetFactory(
+            allocator,
+            NativeMemoryPool.createListenable(DirectReservationListener.instance()),
+            fileFormat,
+            fileUri
+        ).use { datasetFactory ->
+            datasetFactory.finish().use { dataset ->
+                dataset.newScan(scanOptions).use { scanner ->
+                    scanner.scanBatches().use { reader ->
+                        return readArrow(reader, nullability)
+                    }
+                }
+            }
+        }
+    }
+}

dataframe-arrow/src/test/kotlin/org/jetbrains/kotlinx/dataframe/io/ArrowKtTest.kt

@@ -583,4 +583,17 @@ internal class ArrowKtTest {
         val arrowStreamReader = ArrowStreamReader(ipcInputStream, RootAllocator())
         arrowStreamReader.toDataFrame() shouldBe expected
     }
+
+    @Test
+    fun testReadParquet(){
+        val path = testResource("test.arrow.parquet").path
+        val dataFrame = DataFrame.readParquet(URL("file:$path"))
+        dataFrame.rowsCount() shouldBe 300
+        assertEstimations(
+            exampleFrame = dataFrame,
+            expectedNullable = false,
+            hasNulls = false,
+            fromParquet = true
+        )
+    }
 }

dataframe-arrow/src/test/kotlin/org/jetbrains/kotlinx/dataframe/io/exampleEstimatesAssertions.kt

@@ -18,7 +18,12 @@ import kotlin.reflect.typeOf
  * Assert that we have got the same data that was originally saved on example creation.
  * Example generation project is currently located at https://github.com/Kopilov/arrow_example
  */
-internal fun assertEstimations(exampleFrame: AnyFrame, expectedNullable: Boolean, hasNulls: Boolean) {
+internal fun assertEstimations(
+    exampleFrame: AnyFrame,
+    expectedNullable: Boolean,
+    hasNulls: Boolean,
+    fromParquet: Boolean = false
+) {
     /**
      * In [exampleFrame] we get two concatenated batches. To assert the estimations, we should transform frame row number to batch row number
      */
@@ -129,10 +134,23 @@ internal fun assertEstimations(exampleFrame: AnyFrame, expectedNullable: Boolean
         assertValueOrNull(iBatch(i), element, LocalDate.ofEpochDay(iBatch(i).toLong() * 30))
     }
 
-    val datetimeCol = exampleFrame["date64"] as DataColumn<LocalDateTime?>
-    datetimeCol.type() shouldBe typeOf<LocalDateTime>().withNullability(expectedNullable)
-    datetimeCol.forEachIndexed { i, element ->
-        assertValueOrNull(iBatch(i), element, LocalDateTime.ofEpochSecond(iBatch(i).toLong() * 60 * 60 * 24 * 30, 0, ZoneOffset.UTC))
+    /**
+     *
+     *
+     */
+    if (fromParquet){
+        //parquet format have only one type of date: https://github.com/apache/parquet-format/blob/master/LogicalTypes.md#date without time
+        val datetimeCol = exampleFrame["date64"] as DataColumn<LocalDate?>
+        datetimeCol.type() shouldBe typeOf<LocalDate>().withNullability(expectedNullable)
+        datetimeCol.forEachIndexed { i, element ->
+            assertValueOrNull(iBatch(i), element, LocalDate.ofEpochDay(iBatch(i).toLong() * 30))
+        }
+    }else {
+        val datetimeCol = exampleFrame["date64"] as DataColumn<LocalDateTime?>
+        datetimeCol.type() shouldBe typeOf<LocalDateTime>().withNullability(expectedNullable)
+        datetimeCol.forEachIndexed { i, element ->
+            assertValueOrNull(iBatch(i), element, LocalDateTime.ofEpochSecond(iBatch(i).toLong() * 60 * 60 * 24 * 30, 0, ZoneOffset.UTC))
+        }
     }
 
     val timeSecCol = exampleFrame["time32_seconds"] as DataColumn<LocalTime?>

dataframe-arrow/src/test/resources/test.arrow.parquet

@@ -30,7 +30,7 @@ sl4j = "2.0.7"
 junit = "4.13.2"
 kotestAsserions = "4.6.3"
 jsoup = "1.14.3"
-arrow = "11.0.0"
+arrow = "15.0.0"
 docProcessor = "0.2.3"
 simpleGit = "2.0.3"
 
@@ -65,6 +65,7 @@ jsoup = { module = "org.jsoup:jsoup", version.ref = "jsoup" }
 arrow-format = { group = "org.apache.arrow", name = "arrow-format", version.ref = "arrow" }
 arrow-vector = { group = "org.apache.arrow", name = "arrow-vector", version.ref = "arrow" }
 arrow-memory = { group = "org.apache.arrow", name = "arrow-memory-unsafe", version.ref = "arrow" }
+arrow-dataset = { group = "org.apache.arrow", name = "arrow-dataset", version.ref = "arrow" }
 
 kotlinpoet = { group = "com.squareup", name = "kotlinpoet", version.ref = "kotlinpoet" }
 swagger = { group = "io.swagger.parser.v3", name = "swagger-parser", version.ref = "openapi" }