Add ppl-spark-extension optimzer support & mvn publish

.github/workflows/snapshot-publish.yml

@@ -29,6 +29,7 @@ jobs:
       - name: Publish to Local Maven
         run: |
           sbt standaloneCosmetic/publishM2
+          sbt sparkPPLCosmetic/publishM2
           sbt sparkSqlApplicationCosmetic/publishM2
 
       - uses: actions/checkout@v3

README.md

@@ -35,6 +35,11 @@ To use PPL to Spark translation, you can run Spark with PPL extension:
 spark-sql --conf "spark.sql.extensions=org.opensearch.flint.FlintPPLSparkExtensions"
 ```
 
+### Running With both Extension 
+```
+spark-sql --conf "spark.sql.extensions='org.opensearch.flint.FlintPPLSparkExtensions, org.opensearch.flint.FlintSparkExtensions'"
+```
+
 ## Build
 
 To build and run this application with Spark, you can run:

docs/PPL-on-Spark.md

@@ -0,0 +1,59 @@
+# Running PPL On Spark Reference Manual
+
+## Overview
+
+This module provides the support for running [PPL](https://github.com/opensearch-project/piped-processing-language) queries on Spark using direct logical plan
+translation between PPL's logical plan to Spark's Catalyst logical plan.
+
+### What is PPL ?
+OpenSearch PPL, or Pipe Processing Language, is a query language used with the OpenSearch platform and now Apache Spark.
+PPL allows users to retrieve, query, and analyze data by using commands that are piped together, making it easier to understand and compose complex queries.
+Its syntax is inspired by Unix pipes, which enables chaining of commands to transform and process data. 
+With PPL, users can filter, aggregate, and visualize data in multiple datasources in a more intuitive manner compared to traditional query languages
+
+### Context
+
+The next concepts are the main purpose of introduction this functionality:
+- Transforming PPL to become OpenSearch default query language (specifically for logs/traces/metrics signals)
+- Promoting PPL as a viable candidate for the proposed  CNCF Observability universal query language.
+- Seamlessly Interact with different datasources such as S3 / Prometheus / data-lake leveraging spark execution.
+- Using spark's federative capabilities as a general purpose query engine to facilitate complex queries including joins 
+- Improve and promote PPL to become extensible and general purpose query language to be adopted by the community
+
+
+### Running PPL Commands:
+
+In order to run PPL commands, you will need to perform the following tasks:
+
+#### PPL Build & Run
+
+To build and run this PPL in Spark, you can run:
+
+```
+sbt clean sparkPPLCosmetic/publishM2
+```
+then add org.opensearch:opensearch-spark_2.12 when run spark application, for example,
+```
+bin/spark-shell --packages "org.opensearch:opensearch-spark-ppl_2.12:0.1.0-SNAPSHOT"
+```
+
+### PPL Extension Usage
+
+To use PPL to Spark translation, you can run Spark with PPL extension:
+
+```
+spark-sql --conf "spark.sql.extensions=org.opensearch.flint.FlintPPLSparkExtensions"
+```
+
+### Running With both Flint & PPL Extensions
+In order to make use of both flint and ppl extension, one can simply add both jars (`org.opensearch:opensearch-spark-ppl_2.12:0.1.0-SNAPSHOT`,`org.opensearch:opensearch-spark_2.12:0.1.0-SNAPSHOT`) to the cluster's
+classpath.
+
+Next need to configure both extensions :
+```
+spark-sql --conf "spark.sql.extensions='org.opensearch.flint.FlintPPLSparkExtensions, org.opensearch.flint.FlintSparkExtensions'"
+```
+
+Once this is done, spark will allow both extensions to parse the query (SQL / PPL) and allow the correct execution of the query.
+In addition, PPL queries will enjoy the acceleration capabilities supported by the Flint plugins as described [here](index.md)
+

ppl-spark-integration/src/test/scala/org/opensearch/flint/spark/FlintPPLSuite.scala → integ-test/src/test/scala/org/opensearch/flint/spark/ppl/FlintPPLSuite.scala

@@ -3,16 +3,19 @@
  * SPDX-License-Identifier: Apache-2.0
  */
 
-package org.opensearch.flint.spark
+package org.opensearch.flint.spark.ppl
+
+import org.opensearch.flint.spark.{FlintPPLSparkExtensions, FlintSparkExtensions}
 
 import org.apache.spark.SparkConf
 import org.apache.spark.sql.catalyst.expressions.CodegenObjectFactoryMode
 import org.apache.spark.sql.catalyst.optimizer.ConvertToLocalRelation
+import org.apache.spark.sql.flint.config.FlintSparkConf.OPTIMIZER_RULE_ENABLED
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.test.SharedSparkSession
 
 trait FlintPPLSuite extends SharedSparkSession {
-  override protected def sparkConf = {
+  override protected def sparkConf: SparkConf = {
     val conf = new SparkConf()
       .set("spark.ui.enabled", "false")
       .set(SQLConf.CODEGEN_FALLBACK.key, "false")
@@ -21,7 +24,12 @@ trait FlintPPLSuite extends SharedSparkSession {
       // LocalRelation will exercise the optimization rules better by disabling it as
       // this rule may potentially block testing of other optimization rules such as
       // ConstantPropagation etc.
-      .set("spark.sql.extensions", classOf[FlintPPLSparkExtensions].getName)
+      .set(SQLConf.OPTIMIZER_EXCLUDED_RULES.key, ConvertToLocalRelation.ruleName)
+      .set(
+        "spark.sql.extensions",
+        List(classOf[FlintPPLSparkExtensions].getName, classOf[FlintSparkExtensions].getName)
+          .mkString(", "))
+      .set(OPTIMIZER_RULE_ENABLED.key, "false")
     conf
   }
 }

integ-test/src/test/scala/org/opensearch/flint/spark/ppl/FlintSparkPPLAggregationWithSpanITSuite.scala

@@ -5,8 +5,6 @@
 
 package org.opensearch.flint.spark.ppl
 
-import org.opensearch.flint.spark.FlintPPLSuite
-
 import org.apache.spark.sql.{QueryTest, Row}
 import org.apache.spark.sql.catalyst.analysis.{UnresolvedAttribute, UnresolvedFunction, UnresolvedRelation, UnresolvedStar}
 import org.apache.spark.sql.catalyst.expressions.{Alias, Descending, Divide, Floor, Literal, Multiply, SortOrder}
@@ -20,7 +18,7 @@ class FlintSparkPPLAggregationWithSpanITSuite
     with StreamTest {
 
   /** Test table and index name */
-  private val testTable = "default.flint_ppl_test"
+  private val testTable = "spark_catalog.default.flint_ppl_test"
 
   override def beforeAll(): Unit = {
     super.beforeAll()
@@ -92,7 +90,7 @@ class FlintSparkPPLAggregationWithSpanITSuite
     // Define the expected logical plan
     val star = Seq(UnresolvedStar(None))
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
 
     val aggregateExpressions =
       Alias(UnresolvedFunction(Seq("COUNT"), Seq(ageField), isDistinct = false), "count(age)")()
@@ -132,7 +130,7 @@ class FlintSparkPPLAggregationWithSpanITSuite
     // Define the expected logical plan
     val star = Seq(UnresolvedStar(None))
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
 
     val aggregateExpressions =
       Alias(UnresolvedFunction(Seq("AVG"), Seq(ageField), isDistinct = false), "avg(age)")()
@@ -161,7 +159,7 @@ class FlintSparkPPLAggregationWithSpanITSuite
     // Define the expected logical plan
     val star = Seq(UnresolvedStar(None))
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
 
     val aggregateExpressions =
       Alias(UnresolvedFunction(Seq("AVG"), Seq(ageField), isDistinct = false), "avg(age)")()
@@ -203,7 +201,7 @@ class FlintSparkPPLAggregationWithSpanITSuite
     // Define the expected logical plan
     val star = Seq(UnresolvedStar(None))
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
     val countryField = UnresolvedAttribute("country")
     val countryAlias = Alias(countryField, "country")()
 
@@ -239,7 +237,7 @@ class FlintSparkPPLAggregationWithSpanITSuite
     // Define the expected logical plan
     val star = Seq(UnresolvedStar(None))
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
     val countryField = UnresolvedAttribute("country")
     val countryAlias = Alias(countryField, "country")()
 
@@ -272,7 +270,7 @@ class FlintSparkPPLAggregationWithSpanITSuite
     // Define the expected logical plan
     val star = Seq(UnresolvedStar(None))
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
     val countryField = UnresolvedAttribute("country")
     val countryAlias = Alias(countryField, "country")()
 

integ-test/src/test/scala/org/opensearch/flint/spark/ppl/FlintSparkPPLAggregationsITSuite.scala

@@ -5,8 +5,6 @@
 
 package org.opensearch.flint.spark.ppl
 
-import org.opensearch.flint.spark.FlintPPLSuite
-
 import org.apache.spark.sql.{QueryTest, Row}
 import org.apache.spark.sql.catalyst.analysis.{UnresolvedAttribute, UnresolvedFunction, UnresolvedRelation, UnresolvedStar}
 import org.apache.spark.sql.catalyst.expressions.{Alias, Ascending, EqualTo, LessThan, Literal, Not, SortOrder}
@@ -20,7 +18,7 @@ class FlintSparkPPLAggregationsITSuite
     with StreamTest {
 
   /** Test table and index name */
-  private val testTable = "default.flint_ppl_test"
+  private val testTable = "spark_catalog.default.flint_ppl_test"
 
   override def beforeAll(): Unit = {
     super.beforeAll()
@@ -86,7 +84,7 @@ class FlintSparkPPLAggregationsITSuite
     // Define the expected logical plan
     val star = Seq(UnresolvedStar(None))
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
     val aggregateExpressions =
       Seq(Alias(UnresolvedFunction(Seq("AVG"), Seq(ageField), isDistinct = false), "avg(age)")())
     val aggregatePlan = Aggregate(Seq(), aggregateExpressions, table)
@@ -116,7 +114,7 @@ class FlintSparkPPLAggregationsITSuite
     // Define the expected logical plan
     val star = Seq(UnresolvedStar(None))
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
     val filterExpr = LessThan(ageField, Literal(50))
     val filterPlan = Filter(filterExpr, table)
     val aggregateExpressions =
@@ -148,7 +146,7 @@ class FlintSparkPPLAggregationsITSuite
     val star = Seq(UnresolvedStar(None))
     val countryField = UnresolvedAttribute("country")
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
 
     val groupByAttributes = Seq(Alias(countryField, "country")())
     val aggregateExpressions =
@@ -177,7 +175,7 @@ class FlintSparkPPLAggregationsITSuite
     // Define the expected logical plan
     val countryField = UnresolvedAttribute("country")
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
 
     val groupByAttributes = Seq(Alias(countryField, "country")())
     val aggregateExpressions =
@@ -213,7 +211,7 @@ class FlintSparkPPLAggregationsITSuite
     val star = Seq(UnresolvedStar(None))
     val countryField = UnresolvedAttribute("country")
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
 
     val groupByAttributes = Seq(Alias(countryField, "country")())
     val aggregateExpressions =
@@ -248,7 +246,7 @@ class FlintSparkPPLAggregationsITSuite
     val star = Seq(UnresolvedStar(None))
     val countryField = UnresolvedAttribute("country")
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
 
     val groupByAttributes = Seq(Alias(countryField, "country")())
     val aggregateExpressions =
@@ -283,7 +281,7 @@ class FlintSparkPPLAggregationsITSuite
     val star = Seq(UnresolvedStar(None))
     val countryField = UnresolvedAttribute("country")
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
 
     val groupByAttributes = Seq(Alias(countryField, "country")())
     val aggregateExpressions =
@@ -317,7 +315,7 @@ class FlintSparkPPLAggregationsITSuite
     val star = Seq(UnresolvedStar(None))
     val countryField = UnresolvedAttribute("country")
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
 
     val groupByAttributes = Seq(Alias(countryField, "country")())
     val aggregateExpressions =
@@ -358,7 +356,7 @@ class FlintSparkPPLAggregationsITSuite
     val star = Seq(UnresolvedStar(None))
     val countryField = UnresolvedAttribute("country")
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
 
     val groupByAttributes = Seq(Alias(countryField, "country")())
     val aggregateExpressions =
@@ -396,7 +394,7 @@ class FlintSparkPPLAggregationsITSuite
     val stateField = UnresolvedAttribute("state")
     val countryField = UnresolvedAttribute("country")
     val ageField = UnresolvedAttribute("age")
-    val table = UnresolvedRelation(Seq("default", "flint_ppl_test"))
+    val table = UnresolvedRelation(Seq("spark_catalog", "default", "flint_ppl_test"))
 
     val groupByAttributes = Seq(Alias(countryField, "country")())
     val aggregateExpressions =