Delta Lake — Learn free

Self-check

Questions 1–10 of 10

1. What was one of the biggest criticisms of early data lakes that Delta Lake set out to solve?
Question 1A. They could not store unstructured dataB. Their lack of reliability, with no transactional integrity or data consistency on file-based storageC. They were too small to hold enterprise dataD. They required expensive proprietary hardwareE. They could not be queried with Spark
2. What does DML (Data Manipulation Language) refer to?
Question 2A. Operations such as inserts, updates and deletesB. The metadata catalogue of a data lakeC. The JSON transaction logD. A columnar file formatE. A streaming ingestion framework
3. What problem did Apache Spark introduce even though it enabled fast queries and analytics?
Question 3A. It could only process batch workloadsB. It could not read Parquet filesC. It was not ACID-compliant, risking incomplete writes or corrupted data when jobs failed midwayD. It required a relational database underneathE. It stored all data on a single node
4. Who originally developed Delta Lake, and what kind of technology is it?
Question 4A. Cloudera, a Hadoop distributionB. Databricks, an open-source storage layerC. Amazon, a proprietary object storeD. Microsoft, a relational databaseE. Google, a streaming framework
5. On which file format is Delta Lake built, and in what format is its transaction log stored?
Question 5A. Built on CSV, log stored in XMLB. Built on Apache Parquet, log stored in JSONC. Built on Avro, log stored in ParquetD. Built on JSON, log stored in CSVE. Built on ORC, log stored in YAML
6. What does the Delta Log enable?
Question 6A. Compression of Parquet filesB. Transactional guarantees, auditability and rollback by recording every change to the dataC. Conversion of data into relational tablesD. Encryption of data at restE. Automatic dimensional modelling
7. What is the Time Travel feature of Delta Lake?
Question 7A. Scheduling jobs to run at a future timeB. Keeping historical versions of data for rollback or auditing, accessible by timestamp or version numberC. Replicating data across time zonesD. Streaming data with sub-second latencyE. Archiving old partitions to tape
8. How does Delta Lake support Change Data Capture (CDC)?
Question 8A. By scanning the whole data set on every runB. Through the Delta Log, so downstream systems can consume incremental changes rather than reprocessing entire data setsC. By emailing change reports to analystsD. By locking tables during updatesE. By storing changes in a separate relational database
9. Which of the following is NOT one of the innovations Delta Lake introduced?
Question 9A. ACID transactionsB. Unified batch and streamingC. Schema enforcement and evolutionD. Schema-on-read with no validationE. Upserts and deletes
10. What broader architecture did Delta Lake lay the groundwork for?
Question 10A. The data martB. The data lakehouseC. The OLTP databaseD. The data swampE. The tape archive