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Update to Spark 3.5.
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Ghislain Fourny committed Dec 21, 2023
1 parent 3bebc9e commit b73a128
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Showing 12 changed files with 18 additions and 18 deletions.
14 changes: 7 additions & 7 deletions pom.xml
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<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.12</artifactId>
<version>3.3.2</version>
<version>3.5.0</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.12</artifactId>
<version>3.3.2</version>
<version>3.5.0</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_2.12</artifactId>
<version>3.3.2</version>
<version>3.5.0</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-aws</artifactId>
<version>3.3.2</version>
<version>3.3.6</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-avro_2.12</artifactId>
<version>3.3.2</version>
<version>3.4.0</version>
</dependency>
<dependency>
<groupId>org.antlr</groupId>
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<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-text</artifactId>
<version>1.6</version>
<version>1.10.0</version>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-lang3</artifactId>
<version>3.9</version>
<version>3.12.0</version>
</dependency>
<dependency>
<groupId>commons-io</groupId>
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2 changes: 1 addition & 1 deletion src/main/java/org/rumbledb/items/Base64BinaryItem.java
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import com.esotericsoftware.kryo.Kryo;
import com.esotericsoftware.kryo.io.Input;
import com.esotericsoftware.kryo.io.Output;
import org.apache.commons.lang.StringUtils;
import org.apache.commons.lang3.StringUtils;
import java.util.Base64;
import org.rumbledb.api.Item;
import org.rumbledb.exceptions.ExceptionMetadata;
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2 changes: 1 addition & 1 deletion src/main/java/org/rumbledb/items/DoubleItem.java
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import com.esotericsoftware.kryo.io.Input;
import com.esotericsoftware.kryo.io.Output;

import org.apache.commons.lang.StringUtils;
import org.apache.commons.lang3.StringUtils;
import org.rumbledb.api.Item;
import org.rumbledb.exceptions.ExceptionMetadata;
import org.rumbledb.exceptions.IteratorFlowException;
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2 changes: 1 addition & 1 deletion src/main/java/org/rumbledb/items/FloatItem.java
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import com.esotericsoftware.kryo.io.Input;
import com.esotericsoftware.kryo.io.Output;

import org.apache.commons.lang.StringUtils;
import org.apache.commons.lang3.StringUtils;
import org.rumbledb.api.Item;
import org.rumbledb.exceptions.ExceptionMetadata;
import org.rumbledb.exceptions.IteratorFlowException;
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package org.rumbledb.runtime.functions.strings;

import org.apache.commons.lang.StringUtils;
import org.apache.commons.lang3.StringUtils;
import org.rumbledb.api.Item;
import org.rumbledb.context.DynamicContext;
import org.rumbledb.context.Name;
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import org.apache.commons.codec.binary.Base64;
import org.apache.commons.codec.binary.Hex;
import org.apache.commons.lang.StringUtils;
import org.apache.commons.lang3.StringUtils;
import org.rumbledb.api.Item;
import org.rumbledb.context.DynamicContext;
import org.rumbledb.context.RuntimeStaticContext;
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package sparksoniq.spark.ml;

import org.apache.commons.lang.StringUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.spark.ml.Estimator;
import org.apache.spark.ml.Transformer;
import org.apache.spark.ml.linalg.VectorUDT;
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package sparksoniq.spark.ml;

import org.apache.commons.lang.StringUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.spark.ml.Transformer;
import org.apache.spark.ml.linalg.VectorUDT;
import org.apache.spark.ml.param.ParamMap;
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2 changes: 1 addition & 1 deletion src/test/java/iq/base/AnnotationsTestsBase.java
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package iq.base;

import org.apache.commons.lang.exception.ExceptionUtils;
import org.apache.commons.lang3.exception.ExceptionUtils;
import org.junit.Assert;
import org.rumbledb.api.Item;
import org.rumbledb.api.Rumble;
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(:JIQS: ShouldRun; Output="({ "id" : 0, "label" : 1, "col1" : -1, "col2" : 1.5, "col3" : 1.3, "features" : [ -1, 1.5, 1.3 ], "features2" : [ 0.6811443247067492, -1.6574062675838126 ], "rawPrediction" : [ -37.806767087840996, 37.806767087840996 ], "probability" : [ 3.808287043115909E-17, 1 ], "ocol1" : 1 }, { "id" : 1, "label" : 0, "col1" : 3, "col2" : 2, "col3" : -0.1, "features" : [ 3, 2, -0.1 ], "features2" : [ -2.93898570550277, 0.48441694826197534 ], "rawPrediction" : [ 37.56770709258572, -37.56770709258572 ], "probability" : [ 1, 0 ], "ocol1" : 0 }, { "id" : 2, "label" : 1, "col1" : 0, "col2" : 2.2, "col3" : -1.5, "features" : [ 0, 2.2, -1.5 ], "features2" : [ 0.28609394877170796, 1.1822492465709793 ], "rawPrediction" : [ -19.16835344100661, 19.16835344100661 ], "probability" : [ 4.734671708106428E-9, 0.9999999952653283 ], "ocol1" : 1 })" :)
(:JIQS: ShouldRun; Output="({ "id" : 0, "label" : 1, "col1" : -1, "col2" : 1.5, "col3" : 1.3, "features" : [ -1, 1.5, 1.3 ], "features2" : [ 0.6811443247067493, -1.6574062675838126 ], "rawPrediction" : [ -37.806767087841095, 37.806767087841095 ], "probability" : [ 3.80828704311553E-17, 1 ], "ocol1" : 1 }, { "id" : 1, "label" : 0, "col1" : 3, "col2" : 2, "col3" : -0.1, "features" : [ 3, 2, -0.1 ], "features2" : [ -2.9389857055027706, 0.48441694826197546 ], "rawPrediction" : [ 37.56770709258579, -37.56770709258579 ], "probability" : [ 1, 0 ], "ocol1" : 0 }, { "id" : 2, "label" : 1, "col1" : 0, "col2" : 2.2, "col3" : -1.5, "features" : [ 0, 2.2, -1.5 ], "features2" : [ 0.28609394877170796, 1.1822492465709793 ], "rawPrediction" : [ -19.168353441006694, 19.168353441006694 ], "probability" : [ 4.734671708106025E-9, 0.9999999952653283 ], "ocol1" : 1 })" :)
let $vector-assembler := get-transformer("VectorAssembler")
let $training-data := (
{"id": 0, "label": 1, "col1": 0.0, "col2": 1.1, "col3": 0.1},
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(:JIQS: ShouldRun; Output="({ "id" : 0, "label" : 1, "col1" : -1, "col2" : 1.5, "col3" : 1.3, "features" : [ -1, 1.5, 1.3 ], "features2" : [ 0.6811443247067492, -1.6574062675838126 ], "rawPrediction" : [ -37.806767087840996, 37.806767087840996 ], "probability" : [ 3.808287043115909E-17, 1 ], "ocol1" : 1 }, { "id" : 1, "label" : 0, "col1" : 3, "col2" : 2, "col3" : -0.1, "features" : [ 3, 2, -0.1 ], "features2" : [ -2.93898570550277, 0.48441694826197534 ], "rawPrediction" : [ 37.56770709258572, -37.56770709258572 ], "probability" : [ 1, 0 ], "ocol1" : 0 }, { "id" : 2, "label" : 1, "col1" : 0, "col2" : 2.2, "col3" : -1.5, "features" : [ 0, 2.2, -1.5 ], "features2" : [ 0.28609394877170796, 1.1822492465709793 ], "rawPrediction" : [ -19.16835344100661, 19.16835344100661 ], "probability" : [ 4.734671708106428E-9, 0.9999999952653283 ], "ocol1" : 1 })" :)
(:JIQS: ShouldRun; Output="({ "id" : 0, "label" : 1, "col1" : -1, "col2" : 1.5, "col3" : 1.3, "features" : [ -1, 1.5, 1.3 ], "features2" : [ 0.6811443247067493, -1.6574062675838126 ], "rawPrediction" : [ -37.806767087841095, 37.806767087841095 ], "probability" : [ 3.80828704311553E-17, 1 ], "ocol1" : 1 }, { "id" : 1, "label" : 0, "col1" : 3, "col2" : 2, "col3" : -0.1, "features" : [ 3, 2, -0.1 ], "features2" : [ -2.9389857055027706, 0.48441694826197546 ], "rawPrediction" : [ 37.56770709258579, -37.56770709258579 ], "probability" : [ 1, 0 ], "ocol1" : 0 }, { "id" : 2, "label" : 1, "col1" : 0, "col2" : 2.2, "col3" : -1.5, "features" : [ 0, 2.2, -1.5 ], "features2" : [ 0.28609394877170796, 1.1822492465709793 ], "rawPrediction" : [ -19.168353441006694, 19.168353441006694 ], "probability" : [ 4.734671708106025E-9, 0.9999999952653283 ], "ocol1" : 1 })" :)
let $vector-assembler := get-transformer("VectorAssembler")(?, { "inputCols" : [ "col1", "col2", "col3" ], "outputCol" : "features" })
let $training-data := (
{"id": 0, "label": 1, "col1": 0.0, "col2": 1.1, "col3": 0.1},
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@@ -1,4 +1,4 @@
(:JIQS: ShouldRun; Output="({ "id" : 0, "label" : 1, "col1" : -1, "col2" : 1.5, "col3" : 1.3, "features" : [ -1, 1.5, 1.3 ], "features2" : [ 0.6811443247067492, -1.6574062675838126 ], "rawPrediction" : [ -37.806767087840996, 37.806767087840996 ], "probability" : [ 3.808287043115909E-17, 1 ], "ocol1" : 1 }, { "id" : 1, "label" : 0, "col1" : 3, "col2" : 2, "col3" : -0.1, "features" : [ 3, 2, -0.1 ], "features2" : [ -2.93898570550277, 0.48441694826197534 ], "rawPrediction" : [ 37.56770709258572, -37.56770709258572 ], "probability" : [ 1, 0 ], "ocol1" : 0 }, { "id" : 2, "label" : 1, "col1" : 0, "col2" : 2.2, "col3" : -1.5, "features" : [ 0, 2.2, -1.5 ], "features2" : [ 0.28609394877170796, 1.1822492465709793 ], "rawPrediction" : [ -19.16835344100661, 19.16835344100661 ], "probability" : [ 4.734671708106428E-9, 0.9999999952653283 ], "ocol1" : 1 })" :)
(:JIQS: ShouldRun; Output="({ "id" : 0, "label" : 1, "col1" : -1, "col2" : 1.5, "col3" : 1.3, "features" : [ -1, 1.5, 1.3 ], "features2" : [ 0.6811443247067493, -1.6574062675838126 ], "rawPrediction" : [ -37.806767087841095, 37.806767087841095 ], "probability" : [ 3.80828704311553E-17, 1 ], "ocol1" : 1 }, { "id" : 1, "label" : 0, "col1" : 3, "col2" : 2, "col3" : -0.1, "features" : [ 3, 2, -0.1 ], "features2" : [ -2.9389857055027706, 0.48441694826197546 ], "rawPrediction" : [ 37.56770709258579, -37.56770709258579 ], "probability" : [ 1, 0 ], "ocol1" : 0 }, { "id" : 2, "label" : 1, "col1" : 0, "col2" : 2.2, "col3" : -1.5, "features" : [ 0, 2.2, -1.5 ], "features2" : [ 0.28609394877170796, 1.1822492465709793 ], "rawPrediction" : [ -19.168353441006694, 19.168353441006694 ], "probability" : [ 4.734671708106025E-9, 0.9999999952653283 ], "ocol1" : 1 })" :)

declare type local:mytype as {
"id": "integer", "label": "integer", "col1": "decimal", "col2": "decimal", "col3": "decimal"
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