• pip install pyspark and installing the latest version of Apache Spark leads to errors when calling pyspark.sql.DataFrame.show() methods of DataFrame objects.
• pip install pyspark and installing an older version of Apache Spark, i.e. having a version mismatch between PySpark and Apache Spark, leads to errors even when instantiating a SparkSession.
• pip install pyspark==3.3.4 previously led to an error - the system was unable to build wheels for the package. Now, it seems to install that way, but behaves the same as in the previous case.
• Trying to build the 3.3.4 PySpark package manually with ./build/mvn using Bash from the appropriate directory led to Caused by: org.apache.maven.plugin.PluginExecutionException: Execution scala-compile-first of goal net.alchim31.maven:scala-maven-plu gin:4.4.0:compile failed.

Running this code after having installed this stuff as in case 3:

from pyspark.sql import SparkSession
from datetime import datetime, date
import pandas as pd
from pyspark.sql import Row

spark = SparkSession.builder.getOrCreate()

df = spark.createDataFrame([
    Row(a=1, b=2., c='string1', d=date(2000, 1, 1), e=datetime(2000, 1, 1, 12, 0)),
    Row(a=2, b=3., c='string2', d=date(2000, 2, 1), e=datetime(2000, 1, 2, 12, 0)),
    Row(a=4, b=5., c='string3', d=date(2000, 3, 1), e=datetime(2000, 1, 3, 12, 0))
])
df.printSchema()
df.show()

leads to this:

Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Traceback (most recent call last):
  File "[python file path]", line 6, in <module>
    spark = SparkSession.builder.getOrCreate()
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "[python file path]", line 269, in getOrCreate
    sc = SparkContext.getOrCreate(sparkConf)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "[python file path]", line 483, in getOrCreate
    SparkContext(conf=conf or SparkConf())
  File "[python file path]", line 197, in __init__
    self._do_init(
  File "[python file path]", line 282, in _do_init
    self._jsc = jsc or self._initialize_context(self._conf._jconf)
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "[python file path]", line 402, in _initialize_context
    return self._jvm.JavaSparkContext(jconf)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "[python file path]", line 1585, in __call__
    return_value = get_return_value(
                   ^^^^^^^^^^^^^^^^^
  File "[python file path]", line 326, in get_return_value
    raise Py4JJavaError(
py4j.protocol.Py4JJavaError: An error occurred while calling None.org.apache.spark.api.java.JavaSparkContext.
: java.lang.ExceptionInInitializerError
	at org.apache.spark.unsafe.array.ByteArrayMethods.<clinit>(ByteArrayMethods.java:56)
	at org.apache.spark.memory.MemoryManager.defaultPageSizeBytes$lzycompute(MemoryManager.scala:264)
	at org.apache.spark.memory.MemoryManager.defaultPageSizeBytes(MemoryManager.scala:254)
	at org.apache.spark.memory.MemoryManager.$anonfun$pageSizeBytes$1(MemoryManager.scala:273)
	at scala.runtime.java8.JFunction0$mcJ$sp.apply(JFunction0$mcJ$sp.java:23)
	at scala.Option.getOrElse(Option.scala:189)
	at org.apache.spark.memory.MemoryManager.<init>(MemoryManager.scala:273)
	at org.apache.spark.memory.UnifiedMemoryManager.<init>(UnifiedMemoryManager.scala:58)
	at org.apache.spark.memory.UnifiedMemoryManager$.apply(UnifiedMemoryManager.scala:207)
	at org.apache.spark.SparkEnv$.create(SparkEnv.scala:320)
	at org.apache.spark.SparkEnv$.createDriverEnv(SparkEnv.scala:194)
	at org.apache.spark.SparkContext.createSparkEnv(SparkContext.scala:279)
	at org.apache.spark.SparkContext.<init>(SparkContext.scala:464)
	at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
	at java.base/jdk.internal.reflect.DirectConstructorHandleAccessor.newInstance(DirectConstructorHandleAccessor.java:62)
	at java.base/java.lang.reflect.Constructor.newInstanceWithCaller(Constructor.java:502)
	at java.base/java.lang.reflect.Constructor.newInstance(Constructor.java:486)
	at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
	at py4j.Gateway.invoke(Gateway.java:238)
	at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
	at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
	at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
	at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
	at java.base/java.lang.Thread.run(Thread.java:1570)
Caused by: java.lang.IllegalStateException: java.lang.NoSuchMethodException: java.nio.DirectByteBuffer.<init>(long,int)
	at org.apache.spark.unsafe.Platform.<clinit>(Platform.java:113)
	... 25 more
Caused by: java.lang.NoSuchMethodException: java.nio.DirectByteBuffer.<init>(long,int)
	at java.base/java.lang.Class.getConstructor0(Class.java:3784)
	at java.base/java.lang.Class.getDeclaredConstructor(Class.java:2955)
	at org.apache.spark.unsafe.Platform.<clinit>(Platform.java:71)
	... 25 more

SUCCESS: The process with PID 21224 (child process of PID 9020) has been terminated.
SUCCESS: The process with PID 9020 (child process of PID 15684) has been terminated.
SUCCESS: The process with PID 15684 (child process of PID 4980) has been terminated.

Process finished with exit code 1

System environmental variables JAVA_HOME, HADOOP_HOME, SPARK_HOME are configured. The relevant binary directories are included in the Path system environmental variable.
PYTHON_SPARK is set to python.

EDIT: Great, and now Maven can't even attempt to build the package and throws the error

Error occurred during initialization of VM
Could not reserve enough space for 2097152KB object heap

Just great.

Just in case, if I install the library the first way, for the same piece of code the logs start with this:

Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
root
 |-- a: long (nullable = true)
 |-- b: double (nullable = true)
 |-- c: string (nullable = true)
 |-- d: date (nullable = true)
 |-- e: timestamp (nullable = true)

24/07/22 19:04:46 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
	at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:612)
	at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:594)
	at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38)
	at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:789)
	at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:766)
	at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:525)
	at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:491)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCo*removed*tage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
	at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:893)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:893)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:367)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:331)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
	at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:166)
	at org.apache.spark.scheduler.Task.run(Task.scala:141)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
	at java.base/java.lang.Thread.run(Thread.java:842)
Caused by: java.io.EOFException
	at java.base/java.io.DataInputStream.readInt(DataInputStream.java:398)
	at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:774)
	... 26 more

I do not have a programming setup on my Linux OS yet, although I do consider on trying to do this inside a VM. That will be a bit painful, though, as Virtual Box doesn't seem to allow for much graphics memory, meaning that the framerate will be low.

If things go dire and I will fail to find any sort of way out, I will just have to ask other people to run my code instead, ugh.