78 real Warehousing questions from the Data Engineering bank, as asked in Indian campus drives and tech interviews. Every question has a verified answer and an AI-tutor explanation on placd — free to start.
1. What is Snowflake micro-partition?
Mid
A.an automatic ~50-500MB columnar unit with min/max stats for pruning
B.A cloud-warehouse design where data sits in shared storage and elastic compute scales independently, so you pay for each separately.
C.Massively parallel processing, an architecture that distributes data and query work across many nodes that compute in parallel, the basis of cloud warehouses.
D.Redshift Workload Management, which routes queries into queues with memory and concurrency settings; automatic WLM tunes this dynamically.
A.Snowflake micro-partition — an independent compute cluster, separate from storage
B.Snowflake micro-partition — A fact table that records the occurrence of an event or a coverage relationship with no numeric measures, used for counting events or capturing eligibility.
C.Snowflake micro-partition — copying a small table to every node to avoid redistribution
D.Snowflake micro-partition — an automatic ~50-500MB columnar unit with min/max stats for pruning
A.an independent compute cluster, separate from storage
B.splitting a table by date/integer range to cut bytes scanned
C.sorting data within partitions by up to four columns
D.A fact table that records the occurrence of an event or a coverage relationship with no numeric measures, used for counting events or capturing eligibility.
A.Snowflake virtual warehouse — A fact table tracking a process with multiple milestones, where rows are updated as each step completes, used for pipelines like order fulfillment.
B.Snowflake virtual warehouse — a virtual CPU unit BigQuery uses to execute SQL
C.Snowflake virtual warehouse — an independent compute cluster, separate from storage
D.Snowflake virtual warehouse — Auto-maintained min/max metadata per block (Redshift) or micro-partition that lets the engine skip blocks not matching a filter.
A.Snowflake Time Travel — A Redshift node type that separates compute from managed storage (RMS), letting you scale compute without overprovisioning storage.
B.Snowflake Time Travel — querying or restoring historical table data within a retention window
C.Snowflake Time Travel — A warehouse feature that spins up transient extra compute to absorb query spikes, keeping latency stable under high concurrency.
D.Snowflake Time Travel — an independent compute cluster, separate from storage
A.zero-copy cloning — an instant metadata-only copy of a table/schema/database
B.zero-copy cloning — A Redshift node type that separates compute from managed storage (RMS), letting you scale compute without overprovisioning storage.
C.zero-copy cloning — A small dimension that consolidates assorted low-cardinality flags and indicators into one table to keep fact tables narrow.
D.zero-copy cloning — A fact table that records the occurrence of an event or a coverage relationship with no numeric measures, used for counting events or capturing eligibility.
A.BigQuery partitioning — an instant metadata-only copy of a table/schema/database
B.BigQuery partitioning — splitting a table by date/integer range to cut bytes scanned
C.BigQuery partitioning — Auto-maintained min/max metadata per block (Redshift) or micro-partition that lets the engine skip blocks not matching a filter.
D.BigQuery partitioning — A fact table tracking a process with multiple milestones, where rows are updated as each step completes, used for pipelines like order fulfillment.
A.BigQuery clustering — an automatic ~50-500MB columnar unit with min/max stats for pruning
B.BigQuery clustering — sorting data within partitions by up to four columns
C.BigQuery clustering — co-locating rows with the same key on the same node for joins
D.BigQuery clustering — Two distributed join strategies: broadcast copies a small table to every node, shuffle redistributes both tables by join key across nodes.
A.BigQuery slot — An architecture that adds warehouse-grade management (ACID, governance, BI) directly on open data-lake storage via open table formats.
B.BigQuery slot — copying a small table to every node to avoid redistribution
C.BigQuery slot — A Redshift feature that queries data directly in S3 without loading it, extending the warehouse over the data lake.
D.BigQuery slot — a virtual CPU unit BigQuery uses to execute SQL
A.A fact table that records the occurrence of an event or a coverage relationship with no numeric measures, used for counting events or capturing eligibility.
B.co-locating rows with the same key on the same node for joins
C.A warehouse feature that spins up transient extra compute to absorb query spikes, keeping latency stable under high concurrency.
D.splitting a table by date/integer range to cut bytes scanned
A.Redshift distribution style KEY — An architecture that adds warehouse-grade management (ACID, governance, BI) directly on open data-lake storage via open table formats.
B.Redshift distribution style KEY — A planner that uses table statistics to estimate row counts and pick the cheapest join order and access path for a query.
C.Redshift distribution style KEY — splitting a table by date/integer range to cut bytes scanned
D.Redshift distribution style KEY — co-locating rows with the same key on the same node for joins
A.copying a small table to every node to avoid redistribution
B.A small dimension that consolidates assorted low-cardinality flags and indicators into one table to keep fact tables narrow.
C.A warehouse cache that returns a previously computed result for an identical query without rescanning, often free and instantaneous.
D.Massively parallel processing, an architecture that distributes data and query work across many nodes that compute in parallel, the basis of cloud warehouses.
A.Redshift distribution style ALL — A managed service that continuously reorganizes table data by clustering keys in the background so users never run manual recluster jobs.
B.Redshift distribution style ALL — copying a small table to every node to avoid redistribution
C.Redshift distribution style ALL — A small dimension that consolidates assorted low-cardinality flags and indicators into one table to keep fact tables narrow.
D.Redshift distribution style ALL — sorting data within partitions by up to four columns
A.A fact table that records the occurrence of an event or a coverage relationship with no numeric measures, used for counting events or capturing eligibility.
B.A managed service that continuously reorganizes table data by clustering keys in the background so users never run manual recluster jobs.
C.A Redshift table property defining physical row ordering so range-restricted scans skip blocks via zone maps; compound or interleaved variants exist.
D.Massively parallel processing, an architecture that distributes data and query work across many nodes that compute in parallel, the basis of cloud warehouses.
29. Which term means: "Massively parallel processing, an architecture that distributes data and query work across many nodes that compute in parallel, the basis of cloud warehouses."?
A.MPP — Massively parallel processing, an architecture that distributes data and query work across many nodes that compute in parallel, the basis of cloud warehouses.
B.MPP — A Redshift feature that queries data directly in S3 without loading it, extending the warehouse over the data lake.
C.MPP — A warehouse cache that returns a previously computed result for an identical query without rescanning, often free and instantaneous.
D.MPP — an automatic ~50-500MB columnar unit with min/max stats for pruning
Showing 30 of 78 Warehousing questions — the full set, with answers, explanations and an AI tutor on every question, is inside.
Free to start
Answers, AI explanations, and a scored voice mock interview
Sign up free to check your answers with explanations, ask the AI tutor anything on any question, and take one full AI mock interview — scored like a real panel.