diff --git a/R/install-dev.sh b/R/install-dev.sh
index d613552718307..9fbc999f2e805 100755
--- a/R/install-dev.sh
+++ b/R/install-dev.sh
@@ -28,6 +28,7 @@
 
 set -o pipefail
 set -e
+set -x
 
 FWDIR="$(cd "`dirname "${BASH_SOURCE[0]}"`"; pwd)"
 LIB_DIR="$FWDIR/lib"
diff --git a/core/pom.xml b/core/pom.xml
index 0af7d673b79eb..ab28a4db22040 100644
--- a/core/pom.xml
+++ b/core/pom.xml
@@ -464,7 +464,7 @@
               </execution>
             </executions>
             <configuration>
-              <executable>..${file.separator}R${file.separator}install-dev${script.extension}</executable>
+              <executable>${project.basedir}${file.separator}..${file.separator}R${file.separator}install-dev${script.extension}</executable>
             </configuration>
           </plugin>
         </plugins>
diff --git a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala
index 76ea8b86c53d2..23b344230e490 100644
--- a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala
@@ -157,20 +157,25 @@ class HadoopRDD[K, V](
       if (conf.isInstanceOf[JobConf]) {
         logDebug("Re-using user-broadcasted JobConf")
         conf.asInstanceOf[JobConf]
-      } else if (HadoopRDD.containsCachedMetadata(jobConfCacheKey)) {
-        logDebug("Re-using cached JobConf")
-        HadoopRDD.getCachedMetadata(jobConfCacheKey).asInstanceOf[JobConf]
       } else {
-        // Create a JobConf that will be cached and used across this RDD's getJobConf() calls in the
-        // local process. The local cache is accessed through HadoopRDD.putCachedMetadata().
-        // The caching helps minimize GC, since a JobConf can contain ~10KB of temporary objects.
-        // Synchronize to prevent ConcurrentModificationException (SPARK-1097, HADOOP-10456).
-        HadoopRDD.CONFIGURATION_INSTANTIATION_LOCK.synchronized {
-          logDebug("Creating new JobConf and caching it for later re-use")
-          val newJobConf = new JobConf(conf)
-          initLocalJobConfFuncOpt.foreach(f => f(newJobConf))
-          HadoopRDD.putCachedMetadata(jobConfCacheKey, newJobConf)
-          newJobConf
+        Option(HadoopRDD.getCachedMetadata(jobConfCacheKey))
+          .map { conf =>
+            logDebug("Re-using cached JobConf")
+            conf.asInstanceOf[JobConf]
+          }
+          .getOrElse {
+            // Create a JobConf that will be cached and used across this RDD's getJobConf() calls in
+            // the local process. The local cache is accessed through HadoopRDD.putCachedMetadata().
+            // The caching helps minimize GC, since a JobConf can contain ~10KB of temporary
+            // objects. Synchronize to prevent ConcurrentModificationException (SPARK-1097,
+            // HADOOP-10456).
+            HadoopRDD.CONFIGURATION_INSTANTIATION_LOCK.synchronized {
+              logDebug("Creating new JobConf and caching it for later re-use")
+              val newJobConf = new JobConf(conf)
+              initLocalJobConfFuncOpt.foreach(f => f(newJobConf))
+              HadoopRDD.putCachedMetadata(jobConfCacheKey, newJobConf)
+              newJobConf
+          }
         }
       }
     }
@@ -360,8 +365,6 @@ private[spark] object HadoopRDD extends Logging {
    */
   def getCachedMetadata(key: String): Any = SparkEnv.get.hadoopJobMetadata.get(key)
 
-  def containsCachedMetadata(key: String): Boolean = SparkEnv.get.hadoopJobMetadata.containsKey(key)
-
   private def putCachedMetadata(key: String, value: Any): Unit =
     SparkEnv.get.hadoopJobMetadata.put(key, value)
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/internal/CatalogImpl.scala b/sql/core/src/main/scala/org/apache/spark/sql/internal/CatalogImpl.scala
index 0b8e53868c999..e3ed419337e86 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/internal/CatalogImpl.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/internal/CatalogImpl.scala
@@ -462,13 +462,20 @@ class CatalogImpl(sparkSession: SparkSession) extends Catalog {
    */
   override def refreshTable(tableName: String): Unit = {
     val tableIdent = sparkSession.sessionState.sqlParser.parseTableIdentifier(tableName)
-    // Temp tables: refresh (or invalidate) any metadata/data cached in the plan recursively.
-    // Non-temp tables: refresh the metadata cache.
-    sessionCatalog.refreshTable(tableIdent)
+    val tableMetadata = sessionCatalog.getTempViewOrPermanentTableMetadata(tableIdent)
+    val table = sparkSession.table(tableIdent)
+
+    if (tableMetadata.tableType == CatalogTableType.VIEW) {
+      // Temp or persistent views: refresh (or invalidate) any metadata/data cached
+      // in the plan recursively.
+      table.queryExecution.analyzed.foreach(_.refresh())
+    } else {
+      // Non-temp tables: refresh the metadata cache.
+      sessionCatalog.refreshTable(tableIdent)
+    }
 
     // If this table is cached as an InMemoryRelation, drop the original
     // cached version and make the new version cached lazily.
-    val table = sparkSession.table(tableIdent)
     if (isCached(table)) {
       // Uncache the logicalPlan.
       sparkSession.sharedState.cacheManager.uncacheQuery(table, blocking = true)
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala
index 53e500ea78fc4..85a88dff20761 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala
@@ -193,12 +193,12 @@ case class RelationConversions(
   private def convert(relation: HiveTableRelation): LogicalRelation = {
     val serde = relation.tableMeta.storage.serde.getOrElse("").toLowerCase(Locale.ROOT)
     if (serde.contains("parquet")) {
-      val options = Map(ParquetOptions.MERGE_SCHEMA ->
+      val options = relation.tableMeta.storage.properties + (ParquetOptions.MERGE_SCHEMA ->
         conf.getConf(HiveUtils.CONVERT_METASTORE_PARQUET_WITH_SCHEMA_MERGING).toString)
       sessionCatalog.metastoreCatalog
         .convertToLogicalRelation(relation, options, classOf[ParquetFileFormat], "parquet")
     } else {
-      val options = Map[String, String]()
+      val options = relation.tableMeta.storage.properties
       sessionCatalog.metastoreCatalog
         .convertToLogicalRelation(relation, options, classOf[OrcFileFormat], "orc")
     }
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetadataCacheSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetadataCacheSuite.scala
index 0c28a1b609bb8..e71aba72c31fe 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetadataCacheSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetadataCacheSuite.scala
@@ -31,14 +31,22 @@ import org.apache.spark.sql.test.SQLTestUtils
 class HiveMetadataCacheSuite extends QueryTest with SQLTestUtils with TestHiveSingleton {
 
   test("SPARK-16337 temporary view refresh") {
-    withTempView("view_refresh") {
+    checkRefreshView(isTemp = true)
+  }
+
+  test("view refresh") {
+    checkRefreshView(isTemp = false)
+  }
+
+  private def checkRefreshView(isTemp: Boolean) {
+    withView("view_refresh") {
       withTable("view_table") {
         // Create a Parquet directory
         spark.range(start = 0, end = 100, step = 1, numPartitions = 3)
           .write.saveAsTable("view_table")
 
-        // Read the table in
-        spark.table("view_table").filter("id > -1").createOrReplaceTempView("view_refresh")
+        val temp = if (isTemp) "TEMPORARY" else ""
+        spark.sql(s"CREATE $temp VIEW view_refresh AS SELECT * FROM view_table WHERE id > -1")
         assert(sql("select count(*) from view_refresh").first().getLong(0) == 100)
 
         // Delete a file using the Hadoop file system interface since the path returned by
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala
index 6b19b5ccb6f24..c1c8281cd75f7 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala
@@ -21,6 +21,8 @@ import java.io.File
 import java.net.URI
 
 import org.apache.hadoop.fs.Path
+import org.apache.parquet.format.converter.ParquetMetadataConverter.NO_FILTER
+import org.apache.parquet.hadoop.ParquetFileReader
 import org.scalatest.BeforeAndAfterEach
 
 import org.apache.spark.SparkException
@@ -30,6 +32,7 @@ import org.apache.spark.sql.catalyst.catalog._
 import org.apache.spark.sql.catalyst.TableIdentifier
 import org.apache.spark.sql.execution.command.{DDLSuite, DDLUtils}
 import org.apache.spark.sql.hive.HiveExternalCatalog
+import org.apache.spark.sql.hive.HiveUtils.{CONVERT_METASTORE_ORC, CONVERT_METASTORE_PARQUET}
 import org.apache.spark.sql.hive.orc.OrcFileOperator
 import org.apache.spark.sql.hive.test.TestHiveSingleton
 import org.apache.spark.sql.internal.{HiveSerDe, SQLConf}
@@ -1438,12 +1441,8 @@ class HiveDDLSuite
         sql("INSERT INTO t SELECT 1")
         checkAnswer(spark.table("t"), Row(1))
         // Check if this is compressed as ZLIB.
-        val maybeOrcFile = path.listFiles().find(!_.getName.endsWith(".crc"))
-        assert(maybeOrcFile.isDefined)
-        val orcFilePath = maybeOrcFile.get.toPath.toString
-        val expectedCompressionKind =
-          OrcFileOperator.getFileReader(orcFilePath).get.getCompression
-        assert("ZLIB" === expectedCompressionKind.name())
+        val maybeOrcFile = path.listFiles().find(_.getName.startsWith("part"))
+        assertCompression(maybeOrcFile, "orc", "ZLIB")
 
         sql("CREATE TABLE t2 USING HIVE AS SELECT 1 AS c1, 'a' AS c2")
         val table2 = spark.sessionState.catalog.getTableMetadata(TableIdentifier("t2"))
@@ -1941,4 +1940,47 @@ class HiveDDLSuite
       }
     }
   }
+
+  private def assertCompression(maybeFile: Option[File], format: String, compression: String) = {
+    assert(maybeFile.isDefined)
+
+    val actualCompression = format match {
+      case "orc" =>
+        OrcFileOperator.getFileReader(maybeFile.get.toPath.toString).get.getCompression.name
+
+      case "parquet" =>
+        val footer = ParquetFileReader.readFooter(
+          sparkContext.hadoopConfiguration, new Path(maybeFile.get.getPath), NO_FILTER)
+        footer.getBlocks.get(0).getColumns.get(0).getCodec.toString
+    }
+
+    assert(compression === actualCompression)
+  }
+
+  Seq(("orc", "ZLIB"), ("parquet", "GZIP")).foreach { case (fileFormat, compression) =>
+    test(s"SPARK-22158 convertMetastore should not ignore table property - $fileFormat") {
+      withSQLConf(CONVERT_METASTORE_ORC.key -> "true", CONVERT_METASTORE_PARQUET.key -> "true") {
+        withTable("t") {
+          withTempPath { path =>
+            sql(
+              s"""
+                |CREATE TABLE t(id int) USING hive
+                |OPTIONS(fileFormat '$fileFormat', compression '$compression')
+                |LOCATION '${path.toURI}'
+              """.stripMargin)
+            val table = spark.sessionState.catalog.getTableMetadata(TableIdentifier("t"))
+            assert(DDLUtils.isHiveTable(table))
+            assert(table.storage.serde.get.contains(fileFormat))
+            assert(table.storage.properties.get("compression") == Some(compression))
+            assert(spark.table("t").collect().isEmpty)
+
+            sql("INSERT INTO t SELECT 1")
+            checkAnswer(spark.table("t"), Row(1))
+            val maybeFile = path.listFiles().find(_.getName.startsWith("part"))
+            assertCompression(maybeFile, fileFormat, compression)
+          }
+        }
+      }
+    }
+  }
 }