Output modes (append, complete, update) in Apache Spark

Introduction

Output modes decide how new data is added or shown in a streaming result. They help control what you see when data keeps coming in.

When you want to add only new rows to your output without changing old data.

When you want to replace the entire output with fresh results every time.

When you want to update existing rows and add new rows in your output.

Syntax

Apache Spark

df.writeStream.outputMode("mode")
  .format("console")
  .start()

Replace "mode" with one of: "append", "complete", or "update".

Output mode controls how the streaming results are written to the sink.

Examples

Shows only new rows added since last output.

Apache Spark

df.writeStream.outputMode("append")
  .format("console")
  .start()

Shows the full result table every time it updates.

Apache Spark

df.writeStream.outputMode("complete")
  .format("console")
  .start()

Shows only rows that changed or are new since last output.

Apache Spark

df.writeStream.outputMode("update")
  .format("console")
  .start()

Sample Program

This program reads streaming data, groups it by 10-second windows, counts rows, and prints the full aggregated result each time it updates using the 'complete' output mode.

Apache Spark

from pyspark.sql import SparkSession
from pyspark.sql.functions import expr

spark = SparkSession.builder.appName("OutputModesExample").getOrCreate()

# Create streaming DataFrame from rate source (rows with timestamp and value)
inputStream = spark.readStream.format("rate").option("rowsPerSecond", 5).load()

# Aggregate count of rows per 10-second window
aggStream = inputStream.groupBy(expr("window(timestamp, '10 seconds')")).count()

# Start query with output mode 'complete' to see full aggregation each time
query = aggStream.writeStream.outputMode("complete")\
  .format("console")\
  .option("truncate", False)\
  .start()

query.awaitTermination(10000)  # Run for 10 seconds
query.stop()
spark.stop()

Important Notes

Append mode only works if you add new rows without updating old ones.

Complete mode outputs the entire result table every time, which can be costly for large data.

Update mode outputs only changed rows but requires sinks that support updates.

Summary

Output modes control how streaming results are shown or saved.

Append adds new rows only, complete shows all results, update shows changed rows.

Choose mode based on your data update needs and sink capabilities.

Practice

1. Which output mode in Apache Spark streaming adds only new rows to the sink without updating existing rows?

easy

A. Update

B. Complete

C. Append

D. Overwrite

Solution

1. Step 1: Understand output modes

   Append mode adds only new rows to the output sink without changing existing data.

2. Step 2: Compare with other modes

   Complete mode outputs the entire result table, and Update mode outputs only changed rows.

3. Final Answer:

   Append -> Option C

4. Quick Check:

   Append = adds new rows only [OK]

Hint: Append means add new rows only, no updates [OK]

Common Mistakes:

• Confusing append with complete mode
• Thinking update mode adds only new rows
• Assuming overwrite is an output mode

2. Which of the following is the correct syntax to set the output mode to 'complete' in a Spark Structured Streaming query?

easy

A. query.writeStream.outputMode("complete")

B. query.writeStream.mode("complete")

C. query.writeStream.setOutputMode("complete")

D. query.writeStream.output_mode("complete")

Solution

1. Step 1: Recall Spark streaming syntax

   The correct method to set output mode is outputMode("mode_name") on writeStream.

2. Step 2: Check options

   query.writeStream.outputMode("complete") uses outputMode("complete"), which is correct syntax. Others use incorrect method names or casing.

3. Final Answer:

   query.writeStream.outputMode("complete") -> Option A

4. Quick Check:

   outputMode("complete") is correct method [OK]

Hint: Use outputMode() method exactly as shown [OK]

Common Mistakes:

• Using mode() instead of outputMode()
• Using underscores instead of camelCase
• Trying setOutputMode() which doesn't exist

3. Given the following code snippet, what will be the output mode behavior?

val query = df.writeStream
  .format("console")
  .outputMode("update")
  .start()

What does the 'update' mode do here?

medium

A. Overwrites the entire sink with new data

B. Outputs the entire result table every time

C. Outputs only new rows added since last trigger

D. Outputs only rows that have changed since last trigger

Solution

1. Step 1: Understand 'update' mode meaning

   Update mode outputs only rows that have changed since the last trigger, not the full table.

2. Step 2: Compare with other modes

   Append outputs only new rows, complete outputs full table, overwrite is not a streaming mode.

3. Final Answer:

   Outputs only rows that have changed since last trigger -> Option D

4. Quick Check:

   Update = changed rows only [OK]

Hint: Update mode shows changed rows only, not full or just new [OK]

Common Mistakes:

• Confusing update with append mode
• Thinking update outputs full table
• Assuming overwrite is a streaming output mode

4. You wrote this Spark streaming code but get an error:

df.writeStream
  .format("console")
  .outputMode("append")
  .start()

The query fails because the DataFrame has aggregations. What is the error and how to fix it?

medium

A. Append mode not allowed with aggregations; use complete mode instead

B. Output mode 'append' is misspelled; fix spelling

C. Format 'console' does not support append mode; use 'memory' format

D. Start method missing awaitTermination(); add it

Solution

1. Step 1: Identify cause of error

   Append mode cannot be used with aggregations because new rows alone can't be identified.

2. Step 2: Fix by changing output mode

   Use complete mode to output full aggregation results instead of append.

3. Final Answer:

   Append mode not allowed with aggregations; use complete mode instead -> Option A

4. Quick Check:

   Aggregations require complete mode, not append [OK]

Hint: Aggregations need complete mode, not append [OK]

Common Mistakes:

• Trying to fix by changing format instead of mode
• Ignoring aggregation restrictions
• Assuming spelling or method call errors

5. You have a streaming query with a stateful aggregation that updates counts per key. You want to output only the changed counts to a database sink that supports updates. Which output mode should you choose and why?

hard

A. Append mode, because it adds only new counts

B. Update mode, because it outputs only changed counts for efficient updates

C. Complete mode, because it outputs all counts every time

D. Overwrite mode, because it replaces all data in the sink

Solution

1. Step 1: Understand the use case

   Stateful aggregation updates counts per key, so some counts change over time.

2. Step 2: Choose output mode for efficient updates

   Update mode outputs only changed rows, ideal for sinks supporting updates to avoid full rewrites.

3. Step 3: Exclude other modes

   Append mode can't handle updates, complete mode outputs full data (less efficient), overwrite replaces all data (not streaming mode).

4. Final Answer:

   Update mode, because it outputs only changed counts for efficient updates -> Option B

5. Quick Check:

   Update mode = changed rows only, best for stateful updates [OK]

Hint: Use update mode for stateful aggregation with update-capable sinks [OK]

Common Mistakes:

• Choosing append mode for updates
• Using complete mode causing full data writes
• Confusing overwrite with streaming output mode