[HUDI-3549] Removing dependency on "spark-avro" (#4955)

Hudi will be taking on promise for it bundles to stay compatible with Spark minor versions (for ex 2.4, 3.1, 3.2): meaning that single build of Hudi (for ex "hudi-spark3.2-bundle") will be compatible with ALL patch versions in that minor branch (in that case 3.2.1, 3.2.0, etc)

To achieve that we'll have to remove (and ban) "spark-avro" as a dependency, which on a few occasions was the root-cause of incompatibility b/w consecutive Spark patch versions (most recently 3.2.1 and 3.2.0, due to this PR).

Instead of bundling "spark-avro" as dependency, we will be copying over some of the classes Hudi depends on and maintain them along the Hudi code-base to make sure we're able to provide for the aforementioned guarantee. To workaround arising compatibility issues we will be applying local patches to guarantee compatibility of Hudi bundles w/in the Spark minor version branches.

Following Hudi modules to Spark minor branches is currently maintained:

"hudi-spark3" -> 3.2.x
"hudi-spark3.1.x" -> 3.1.x
"hudi-spark2" -> 2.4.x
Following classes hierarchies (borrowed from "spark-avro") are maintained w/in these Spark-specific modules to guarantee compatibility with respective minor version branches:

AvroSerializer
AvroDeserializer
AvroUtils
Each of these classes has been correspondingly copied from Spark 3.2.1 (for 3.2.x branch), 3.1.2 (for 3.1.x branch), 2.4.4 (for 2.4.x branch) into their respective modules.

SchemaConverters class in turn is shared across all those modules given its relative stability (there're only cosmetical changes from 2.4.4 to 3.2.1).
All of the aforementioned classes have their corresponding scope of visibility limited to corresponding packages (org.apache.spark.sql.avro, org.apache.spark.sql) to make sure broader code-base does not become dependent on them and instead relies on facades abstracting them.

Additionally, given that Hudi plans on supporting all the patch versions of Spark w/in aforementioned minor versions branches of Spark, additional build steps were added to validate that Hudi could be properly compiled against those versions. Testing, however, is performed against the most recent patch versions of Spark with the help of Azure CI.

Brief change log:
- Removing spark-avro bundling from Hudi by default
- Scaffolded Spark 3.2.x hierarchy
- Bootstrapped Spark 3.1.x Avro serializer/deserializer hierarchy
- Bootstrapped Spark 2.4.x Avro serializer/deserializer hierarchy
- Moved ExpressionCodeGen,ExpressionPayload into hudi-spark module
- Fixed AvroDeserializer to stay compatible w/ both Spark 3.2.1 and 3.2.0
- Modified bot.yml to build full matrix of support Spark versions
- Removed "spark-avro" dependency from all modules
- Fixed relocation of spark-avro classes in bundles to assist in running integ-tests.

hudi-integ-test/README.md

@@ -126,7 +126,7 @@ NOTE : The properties-file should have all the necessary information required to
  information on what properties need to be set, take a look at the test suite section under demo steps.
 ```
 shell$ ./prepare_integration_suite.sh --spark-command
-spark-submit --packages com.databricks:spark-avro_2.11:4.0.0 --master prepare_integration_suite.sh --deploy-mode
+spark-submit --master prepare_integration_suite.sh --deploy-mode
 --properties-file  --class org.apache.hudi.integ.testsuite.HoodieTestSuiteJob target/hudi-integ-test-0.6
 .0-SNAPSHOT.jar --source-class  --source-ordering-field  --input-base-path  --target-base-path  --target-table  --props  --storage-type  --payload-class  --workload-yaml-path  --input-file-size  --<deltastreamer-ingest>
 ```
@@ -198,7 +198,6 @@ Launch a Copy-on-Write job:
 =========================
 ## Run the following command to start the test suite
 spark-submit \
---packages org.apache.spark:spark-avro_2.11:2.4.0 \
 --conf spark.task.cpus=1 \
 --conf spark.executor.cores=1 \
 --conf spark.task.maxFailures=100 \
@@ -245,7 +244,6 @@ Or a Merge-on-Read job:
 =========================
 ## Run the following command to start the test suite
 spark-submit \
---packages org.apache.spark:spark-avro_2.11:2.4.0 \
 --conf spark.task.cpus=1 \
 --conf spark.executor.cores=1 \
 --conf spark.task.maxFailures=100 \
@@ -438,7 +436,6 @@ docker exec -it adhoc-2 /bin/bash
 Sample COW command
 ```
 spark-submit \
---packages org.apache.spark:spark-avro_2.11:2.4.0 \
 --conf spark.task.cpus=1 \
 --conf spark.executor.cores=1 \
 --conf spark.task.maxFailures=100 \