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Load data into Hive table from HDFS or local

Spark/Big Datahard0.5 min read

Reviewed by Aditya Kumar · Last reviewed 2026-03-25

**Why it matters**: At scale, design choices directly impact reliability, latency, and cost. Wrong decisions compound across jobs and teams. Load data into Hive: From HDFS: `LOAD DATA INPATH 'hdfs://path' INTO TABLE t` or `OVERWRITE`. From local: `LOAD DATA LOCAL INPATH...

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Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
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Key Concepts Tested
optimizationpartition
Expert Answer
96 words

Why it matters: At scale, design choices directly impact reliability, latency, and cost. Wrong decisions compound across jobs and teams.

Load data into Hive: From HDFS: LOAD DATA INPATH 'hdfs://path' INTO TABLE t or OVERWRITE. From local: LOAD DATA LOCAL INPATH '/local/path'. For external: CREATE EXTERNAL TABLE t (...) LOCATION 'hdfs://path'. Insert from another table: INSERT INTO t SELECT * FROM s. Best practice: Use external tables for shared data; partition by date; validate before load.

Scalability trade-offs: Partition/parallelism limits; single points of failure; horizontal vs vertical scaling. Cost implications: Sizing, spot vs reserved, optimization ROI.

⚡
Pro Tip

Red Flag: Overwrite without backup. Pro-Move: 'External tables; partition; validate.'

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According to DataEngPrep.tech, this is one of the most frequently asked Spark/Big Data interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.

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