我想在Python中使用三角洲湖。我在Debian 11.6中安装了spark作为独立的和anaconda。
我尝试运行delta lake的代码是：

import pyspark
from delta import *

builder = pyspark.sql.SparkSession.builder.appName("MyApp") \
    .config("spark.sql.extensions", "io.delta.sql.DeltaSparkSessionExtension") \
    .config("spark.sql.catalog.spark_catalog", "org.apache.spark.sql.delta.catalog.DeltaCatalog")

spark = configure_spark_with_delta_pip(builder).getOrCreate()

但是上面的代码出现这个错误：

:: loading settings :: url = jar:file:/usr/bin/spark-3.3.1-bin-hadoop3/jars/ivy-2.5.0.jar!/org/apache/ivy/core/settings/ivysettings.xml

Ivy Default Cache set to: /home/boss/.ivy2/cache
The jars for the packages stored in: /home/boss/.ivy2/jars
io.delta#delta-core_2.12 added as a dependency
:: resolving dependencies :: org.apache.spark#spark-submit-parent-290d27e6-7e29-475f-81b5-1ab1331508fc;1.0
    confs: [default]
    found io.delta#delta-core_2.12;2.2.0 in central
    found io.delta#delta-storage;2.2.0 in central
    found org.antlr#antlr4-runtime;4.8 in central
:: resolution report :: resolve 272ms :: artifacts dl 10ms
    :: modules in use:
    io.delta#delta-core_2.12;2.2.0 from central in [default]
    io.delta#delta-storage;2.2.0 from central in [default]
    org.antlr#antlr4-runtime;4.8 from central in [default]
    ---------------------------------------------------------------------
    |                  |            modules            ||   artifacts   |
    |       conf       | number| search|dwnlded|evicted|| number|dwnlded|
    ---------------------------------------------------------------------
    |      default     |   3   |   0   |   0   |   0   ||   3   |   0   |
    ---------------------------------------------------------------------
:: retrieving :: org.apache.spark#spark-submit-parent-290d27e6-7e29-475f-81b5-1ab1331508fc
    confs: [default]
    0 artifacts copied, 3 already retrieved (0kB/11ms)

23/01/24 04:10:26 WARN NativeCodeLoader: 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).

我怎样才能解决这个问题？