Add PushedFilters to metadata in Parquet DSv2 implementation

// code placeholder
df = spark.createDataFrame([("usr1",17.00, "2018-03-10T15:27:18+00:00"),
                            ("usr1",13.00, "2018-03-11T12:27:18+00:00"),
                            ("usr1",25.00, "2018-03-12T11:27:18+00:00"),
                            ("usr1",20.00, "2018-03-13T15:27:18+00:00"),
                            ("usr1",17.00, "2018-03-14T12:27:18+00:00"),
                            ("usr2",99.00, "2018-03-15T11:27:18+00:00"),
                            ("usr2",156.00, "2018-03-22T11:27:18+00:00"),
                            ("usr2",17.00, "2018-03-31T11:27:18+00:00"),
                            ("usr2",25.00, "2018-03-15T11:27:18+00:00"),
                            ("usr2",25.00, "2018-03-16T11:27:18+00:00")
                            ],
                           ["user","id", "ts"])
df = df.withColumn('ts', df.ts.cast('timestamp'))
df.write.partitionBy("user").parquet("/home/cnali/data/")df2 = spark.read.load("/home/cnali/data/")df2.filter("user=='usr2'").explain(True)

// Spark 2.4 output
== Parsed Logical Plan ==
'Filter ('user = usr2)
+- Relation[id#38,ts#39,user#40] parquet== Analyzed Logical Plan ==
id: double, ts: timestamp, user: string
Filter (user#40 = usr2)
+- Relation[id#38,ts#39,user#40] parquet== Optimized Logical Plan ==
Filter (isnotnull(user#40) && (user#40 = usr2))
+- Relation[id#38,ts#39,user#40] parquet== Physical Plan ==
*(1) FileScan parquet [id#38,ts#39,user#40] Batched: true, Format: Parquet, Location: InMemoryFileIndex[file:/home/cnali/data], PartitionCount: 1, PartitionFilters: [isnotnull(user#40), (user#40 = usr2)], PushedFilters: [], ReadSchema: struct<id:double,ts:timestamp>

// Spark 3.0.0-preview output
== Parsed Logical Plan ==
'Filter ('user = usr2)
+- RelationV2[id#0, ts#1, user#2] parquet file:/home/cnali/data== Analyzed Logical Plan ==
id: double, ts: timestamp, user: string
Filter (user#2 = usr2)
+- RelationV2[id#0, ts#1, user#2] parquet file:/home/cnali/data== Optimized Logical Plan ==
Filter (isnotnull(user#2) AND (user#2 = usr2))
+- RelationV2[id#0, ts#1, user#2] parquet file:/home/cnali/data== Physical Plan ==
*(1) Project [id#0, ts#1, user#2]
+- *(1) Filter (isnotnull(user#2) AND (user#2 = usr2))
   +- *(1) ColumnarToRow
      +- BatchScan[id#0, ts#1, user#2] ParquetScan Location: InMemoryFileIndex[file:/home/cnali/data], ReadSchema: struct<id:double,ts:timestamp>

// pyspark 3 shell output
$ pyspark
Python 3.6.8 (default, Aug  7 2019, 17:28:10) 
[GCC 4.8.5 20150623 (Red Hat 4.8.5-39)] on linux
Type "help", "copyright", "credits" or "license" for more information.
Warning: Ignoring non-spark config property: java.io.dir=/md2k/data1,/md2k/data2,/md2k/data3,/md2k/data4,/md2k/data5,/md2k/data6,/md2k/data7,/md2k/data8
19/12/09 07:05:36 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
19/12/09 07:05:36 WARN SparkConf: Note that spark.local.dir will be overridden by the value set by the cluster manager (via SPARK_LOCAL_DIRS in mesos/standalone/kubernetes and LOCAL_DIRS in YARN).
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /__ / .__/\_,_/_/ /_/\_\   version 3.0.0-preview
      /_/Using Python version 3.6.8 (default, Aug  7 2019 17:28:10)
SparkSession available as 'spark'.

// pyspark 2.4.4 shell output
pyspark
Python 3.6.8 (default, Aug  7 2019, 17:28:10) 
[GCC 4.8.5 20150623 (Red Hat 4.8.5-39)] on linux
Type "help", "copyright", "credits" or "license" for more information.
2019-12-09 07:09:07 WARN  NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /__ / .__/\_,_/_/ /_/\_\   version 2.4.0
      /_/Using Python version 3.6.8 (default, Aug  7 2019 17:28:10)
SparkSession available as 'spark'.