From 048c6ef6c7de957d25adf35d71c9232889e2b4f8 Mon Sep 17 00:00:00 2001 From: alfonsorr Date: Mon, 24 Jun 2024 16:49:24 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20hablapps?= =?UTF-8?q?/doric@dc417660490e3ed428defe17575b9ca28e2293b3=20=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/exclusive.md | 4 ++-- docs/implicits.md | 8 ++++---- docs/quickstart.md | 8 ++++---- docs/validations.md | 2 +- 4 files changed, 11 insertions(+), 11 deletions(-) diff --git a/docs/exclusive.md b/docs/exclusive.md index 39abc0a3..be7fab8a 100644 --- a/docs/exclusive.md +++ b/docs/exclusive.md @@ -103,7 +103,7 @@ val sparkCol = f.expr("array_sort(value, (l, r) -> case " + val doricCol = colArray[Row]("value").sortBy(CName("name"), CNameOrd("age", Desc)) // doricCol: ArrayColumn[Row] = TransformationDoricColumn( -// Kleisli(scala.Function1$$Lambda$3034/0x0000000801380040@1a5d0d94) +// Kleisli(scala.Function1$$Lambda$3064/0x0000000801399840@2d671a7f) // ) dfArrayStruct.select(sparkCol.as("sorted")).show(false) @@ -151,7 +151,7 @@ val mapColDoric = colString("value").matches[String] .caseW(_.length > 4, "error key".lit) .otherwiseNull // mapColDoric: DoricColumn[String] = TransformationDoricColumn( -// Kleisli(scala.Function1$$Lambda$3034/0x0000000801380040@170a5bc8) +// Kleisli(scala.Function1$$Lambda$3064/0x0000000801399840@6484a67c) // ) dfMatch.withColumn("mapResult", mapColDoric).show() diff --git a/docs/implicits.md b/docs/implicits.md index d343c4a7..22c1a07b 100644 --- a/docs/implicits.md +++ b/docs/implicits.md @@ -85,7 +85,7 @@ val complexCol: DoricColumn[Int] = .transform(_ + 1.lit) .aggregate(0.lit)(_ + _) // complexCol: DoricColumn[Int] = TransformationDoricColumn( -// Kleisli(scala.Function1$$Lambda$3034/0x0000000801380040@4cf48c54) +// Kleisli(scala.Function1$$Lambda$3064/0x0000000801399840@75c0df8) // ) dfArrays.select(complexCol as "complexTransformation").show() @@ -277,7 +277,7 @@ The default doric syntax is a little stricter and forces us to transform these v ```scala val colD = colInt("int") + 1.lit // colD: DoricColumn[Int] = TransformationDoricColumn( -// Kleisli(scala.Function1$$Lambda$3034/0x0000000801380040@62779497) +// Kleisli(scala.Function1$$Lambda$3064/0x0000000801399840@67fa61e8) // ) intDF.select(colD).show() @@ -298,11 +298,11 @@ we have to _explicitly_ add the following import statement: import doric.implicitConversions.literalConversion val colSugarD = colInt("int") + 1 // colSugarD: DoricColumn[Int] = TransformationDoricColumn( -// Kleisli(scala.Function1$$Lambda$3034/0x0000000801380040@4351da3) +// Kleisli(scala.Function1$$Lambda$3064/0x0000000801399840@5685ee9) // ) val columConcatLiterals = concat("this", "is","doric") // concat expects DoricColumn[String] values, the conversion puts them as expected // columConcatLiterals: StringColumn = TransformationDoricColumn( -// Kleisli(scala.Function1$$Lambda$3034/0x0000000801380040@587011f0) +// Kleisli(scala.Function1$$Lambda$3064/0x0000000801399840@31a98a8d) // ) intDF.select(colSugarD, columConcatLiterals).show() diff --git a/docs/quickstart.md b/docs/quickstart.md index 1896c972..6f4eac1c 100644 --- a/docs/quickstart.md +++ b/docs/quickstart.md @@ -28,7 +28,7 @@ _Maven_ Doric is committed to use the most modern APIs first. * The latest stable version of doric is 0.0.7. -* The latest experimental version of doric is 0.0.0+1-8c959962-SNAPSHOT. +* The latest experimental version of doric is 0.0.0+1-dc417660-SNAPSHOT. * Doric is compatible with the following Spark versions: | Spark | Scala | Tested | doric | @@ -95,7 +95,7 @@ It's only when we try to construct the DataFrame that an exception is raised at ```scala df // org.apache.spark.sql.AnalysisException: [DATATYPE_MISMATCH.BINARY_OP_DIFF_TYPES] Cannot resolve "(value * true)" due to data type mismatch: the left and right operands of the binary operator have incompatible types ("INT" and "BOOLEAN").; -// 'Project [unresolvedalias((value#365 * true), Some(org.apache.spark.sql.Column$$Lambda$3710/0x0000000801688040@373b6d8d))] +// 'Project [unresolvedalias((value#365 * true), Some(org.apache.spark.sql.Column$$Lambda$3773/0x00000008016b9840@7162999b))] // +- LocalRelation [value#365] // // at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.dataTypeMismatch(package.scala:73) @@ -192,7 +192,7 @@ strDf.select(f.col("str").asDoric[String]).show() strDf.select((f.col("str") + f.lit(true)).asDoric[String]).show() // doric.sem.DoricMultiError: Found 1 error in select // [DATATYPE_MISMATCH.BINARY_OP_DIFF_TYPES] Cannot resolve "(str + true)" due to data type mismatch: the left and right operands of the binary operator have incompatible types ("DOUBLE" and "BOOLEAN").; -// 'Project [unresolvedalias((cast(str#378 as double) + true), Some(org.apache.spark.sql.Column$$Lambda$3710/0x0000000801688040@373b6d8d))] +// 'Project [unresolvedalias((cast(str#378 as double) + true), Some(org.apache.spark.sql.Column$$Lambda$3773/0x00000008016b9840@7162999b))] // +- Project [value#375 AS str#378] // +- LocalRelation [value#375] // @@ -206,7 +206,7 @@ strDf.select((f.col("str") + f.lit(true)).asDoric[String]).show() // at repl.MdocSession$MdocApp$$anonfun$2.apply(quickstart.md:76) // at repl.MdocSession$MdocApp$$anonfun$2.apply(quickstart.md:76) // Caused by: org.apache.spark.sql.AnalysisException: [DATATYPE_MISMATCH.BINARY_OP_DIFF_TYPES] Cannot resolve "(str + true)" due to data type mismatch: the left and right operands of the binary operator have incompatible types ("DOUBLE" and "BOOLEAN").; -// 'Project [unresolvedalias((cast(str#378 as double) + true), Some(org.apache.spark.sql.Column$$Lambda$3710/0x0000000801688040@373b6d8d))] +// 'Project [unresolvedalias((cast(str#378 as double) + true), Some(org.apache.spark.sql.Column$$Lambda$3773/0x00000008016b9840@7162999b))] // +- Project [value#375 AS str#378] // +- LocalRelation [value#375] // diff --git a/docs/validations.md b/docs/validations.md index db0606f5..928fcff8 100644 --- a/docs/validations.md +++ b/docs/validations.md @@ -15,7 +15,7 @@ raising a run-time exception: // Spark List(1,2,3).toDF().select(f.col("id")+1) // org.apache.spark.sql.AnalysisException: [UNRESOLVED_COLUMN.WITH_SUGGESTION] A column or function parameter with name `id` cannot be resolved. Did you mean one of the following? [`value`].; -// 'Project [unresolvedalias(('id + 1), Some(org.apache.spark.sql.Column$$Lambda$3710/0x0000000801688040@373b6d8d))] +// 'Project [unresolvedalias(('id + 1), Some(org.apache.spark.sql.Column$$Lambda$3773/0x00000008016b9840@7162999b))] // +- LocalRelation [value#399] // // at org.apache.spark.sql.errors.QueryCompilationErrors$.unresolvedAttributeError(QueryCompilationErrors.scala:307)