Towards Data Science

NOVEMBER 6, 2024

The appropriate Spark dependencies (spark-core/spark-sql or spark-connect-client-jvm) will be provided later in the Java classpath, depending on the run mode. java -cp "/app/*" com.joom.analytics.sc.client.S3Downloader ${MAIN_APPLICATION_FILE_S3_PATH} ${SPARK_CONNECT_MAIN_APPLICATION_FILE_PATH} # Launch the client application.

Scala 75

Scala Java AWS Coding 75

Towards Data Science

JANUARY 17, 2024

Parquet vs ORC vs Avro vs Delta Lake Photo by Viktor Talashuk on Unsplash The big data world is full of various storage systems, heavily influenced by different file formats. These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction.

Big Data 97

Big Data Data Data Storage SQL 97

Cloud Academy

JANUARY 27, 2022

For example, you can learn about how JSONs are integral to non-relational databases – especially data schemas, and how to write queries using JSON. Some good options are Python (because of its flexibility and being able to handle many data types), as well as Java, Scala, and Go. Rely on the real information to guide you.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

NOVEMBER 22, 2021

show(truncate=False) #Drop duplicates on selected columns dropDisDF = df.dropDuplicates(["department","salary"]) print("Distinct count of department salary : "+str(dropDisDF.count())) dropDisDF.show(truncate=False) } Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Q6.

Hadoop 52

Hadoop Python Datasets Metadata 52

Knowledge Hut

MARCH 22, 2024

Versatility: The versatile nature of MongoDB enables it to easily deal with a broad spectrum of data types , structured and unstructured, and therefore, it is perfect for modern applications that need flexible data schemas. Good Hold on MongoDB and data modeling. Experience with ETL tools and data integration techniques.

MongoDB 52

MongoDB Amazon Web Services Computer Science Education 52

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Variety Hadoop stores structured, semi-structured and unstructured data.

Big Data 52

Big Data Hadoop Relational Database AWS 52

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40