diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala
index c56a5c015f32d..866b382a1d808 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala
@@ -83,7 +83,24 @@ case class EnsureRequirements(conf: SQLConf) extends Rule[SparkPlan] {
         numPartitionsSet.headOption
       }
 
-      val targetNumPartitions = requiredNumPartitions.getOrElse(childrenNumPartitions.max)
+      // If there are non-shuffle children that satisfy the required distribution, we have
+      // some tradeoffs when picking the expected number of shuffle partitions:
+      // 1. We should avoid shuffling these children.
+      // 2. We should have a reasonable parallelism.
+      val nonShuffleChildrenNumPartitions =
+        childrenIndexes.map(children).filterNot(_.isInstanceOf[ShuffleExchangeExec])
+          .map(_.outputPartitioning.numPartitions)
+      val expectedChildrenNumPartitions = if (nonShuffleChildrenNumPartitions.nonEmpty) {
+        // Here we pick the max number of partitions among these non-shuffle children as the
+        // expected number of shuffle partitions. However, if it's smaller than
+        // `conf.numShufflePartitions`, we pick `conf.numShufflePartitions` as the
+        // expected number of shuffle partitions.
+        math.max(nonShuffleChildrenNumPartitions.max, conf.numShufflePartitions)
+      } else {
+        childrenNumPartitions.max
+      }
+
+      val targetNumPartitions = requiredNumPartitions.getOrElse(expectedChildrenNumPartitions)
 
       children = children.zip(requiredChildDistributions).zipWithIndex.map {
         case ((child, distribution), index) if childrenIndexes.contains(index) =>
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/ReduceNumShufflePartitionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/ReduceNumShufflePartitionsSuite.scala
index 4d408cd8ebd70..21ec1ac9bda08 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/ReduceNumShufflePartitionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/ReduceNumShufflePartitionsSuite.scala
@@ -274,6 +274,7 @@ class ReduceNumShufflePartitionsSuite extends SparkFunSuite with BeforeAndAfterA
         .setMaster("local[*]")
         .setAppName("test")
         .set(UI_ENABLED, false)
+        .set(SQLConf.SHUFFLE_PARTITIONS.key, "5")
         .set(SQLConf.SHUFFLE_MAX_NUM_POSTSHUFFLE_PARTITIONS.key, "5")
         .set(SQLConf.ADAPTIVE_EXECUTION_ENABLED.key, "true")
         .set(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key, "-1")
@@ -507,7 +508,7 @@ class ReduceNumShufflePartitionsSuite extends SparkFunSuite with BeforeAndAfterA
             join,
             expectedAnswer.collect())
 
-          // Then, let's make sure we do not reduce number of ppst shuffle partitions.
+          // Then, let's make sure we do not reduce number of post shuffle partitions.
           val finalPlan = join.queryExecution.executedPlan
             .asInstanceOf[AdaptiveSparkPlanExec].executedPlan
           val shuffleReaders = finalPlan.collect {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/BucketedReadSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/BucketedReadSuite.scala
index 7043b6d396977..a585f215ad681 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/sources/BucketedReadSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/BucketedReadSuite.scala
@@ -28,6 +28,7 @@ import org.apache.spark.sql.catalyst.expressions
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.plans.physical.HashPartitioning
 import org.apache.spark.sql.execution.{DataSourceScanExec, SortExec}
+import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec
 import org.apache.spark.sql.execution.datasources.BucketingUtils
 import org.apache.spark.sql.execution.exchange.ShuffleExchangeExec
 import org.apache.spark.sql.execution.joins.SortMergeJoinExec
@@ -382,8 +383,16 @@ abstract class BucketedReadSuite extends QueryTest with SQLTestUtils {
           joined.sort("bucketed_table1.k", "bucketed_table2.k"),
           df1.join(df2, joinCondition(df1, df2), joinType).sort("df1.k", "df2.k"))
 
-        assert(joined.queryExecution.executedPlan.isInstanceOf[SortMergeJoinExec])
-        val joinOperator = joined.queryExecution.executedPlan.asInstanceOf[SortMergeJoinExec]
+        val joinOperator = if (joined.sqlContext.conf.adaptiveExecutionEnabled) {
+          val executedPlan =
+            joined.queryExecution.executedPlan.asInstanceOf[AdaptiveSparkPlanExec].executedPlan
+          assert(executedPlan.isInstanceOf[SortMergeJoinExec])
+          executedPlan.asInstanceOf[SortMergeJoinExec]
+        } else {
+          val executedPlan = joined.queryExecution.executedPlan
+          assert(executedPlan.isInstanceOf[SortMergeJoinExec])
+          executedPlan.asInstanceOf[SortMergeJoinExec]
+        }
 
         // check existence of shuffle
         assert(
@@ -795,4 +804,22 @@ abstract class BucketedReadSuite extends QueryTest with SQLTestUtils {
     }
   }
 
+  test("SPARK-29655 Read bucketed tables obeys spark.sql.shuffle.partitions") {
+    withSQLConf(
+      SQLConf.SHUFFLE_PARTITIONS.key -> "5",
+      SQLConf.SHUFFLE_MAX_NUM_POSTSHUFFLE_PARTITIONS.key -> "7")  {
+      val bucketSpec = Some(BucketSpec(6, Seq("i", "j"), Nil))
+      Seq(false, true).foreach { enableAdaptive =>
+        withSQLConf(SQLConf.ADAPTIVE_EXECUTION_ENABLED.key -> s"$enableAdaptive") {
+          val bucketedTableTestSpecLeft = BucketedTableTestSpec(bucketSpec, expectedShuffle = false)
+          val bucketedTableTestSpecRight = BucketedTableTestSpec(None, expectedShuffle = true)
+          testBucketing(
+            bucketedTableTestSpecLeft = bucketedTableTestSpecLeft,
+            bucketedTableTestSpecRight = bucketedTableTestSpecRight,
+            joinCondition = joinCondition(Seq("i", "j"))
+          )
+        }
+      }
+    }
+  }
 }