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Antony Stubbs (astubbs) wants to merge 2 commits into from
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minor: docs: Fix chart links #506

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START: minor: docs: Fix chart links
astubbs Dec 8, 2022
33d93af
more tests
astubbs Dec 8, 2022
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21 changes: 19 additions & 2 deletions README.adoc
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -288,10 +288,27 @@ These performance comparison results below, even though are based on real perfor
To see how the performance of the tool is related to instance counts, partition counts, key distribution and how it would relate to the vanilla client.
Actual results will vary wildly depending upon the setup being deployed into.

For example, if you have hundreds of thousands of keys in your topic, randomly distributed, even with hundreds of partitions, with only a handful of this wrapper deployed, you will probably see many orders of magnitude performance improvements - massively out performing dozens of vanilla Kafka consumer clients.
For example, if you have hundreds of thousands of keys in your topic, randomly distributed, even with hundreds of partitions, with only a handful of this wrapper deployed, you will probably see many orders of magnitude performance improvements - massively outperforming dozens of vanilla Kafka consumer clients.

.Time taken to process a large number of messages with a Single Parallel Consumer vs a single Kafka Consumer, for different key space sizes. As the number of unique keys in the data set increases, the key ordered Parallel Consumer performance starts to approach that of the unordered Parallel Consumer. The raw Kafka consumer performance remains unaffected by the key distribution.
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=1691474082&format=image[align="center"]
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=1691474082&format=image[align="center"]

test1

.test1
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=1161363385&format=interactive[align="center"]

test1.5: image:https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=1161363385&format=interactive[align="center"]

test2

.test2
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=1161363385&format=image[align="center"]

test3

.test3
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=938493158&format=image[align="center"]

.Consumer group size effect on total processing time vs a single Parallel Consumer. As instances are added to the consumer group, it's performance starts to approach that of the single instance Parallel Consumer. Key ordering is faster than partition ordering, with unordered being the fastest.
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=938493158&format=image[align="center"]
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21 changes: 19 additions & 2 deletions src/docs/README_TEMPLATE.adoc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -286,10 +286,27 @@ These performance comparison results below, even though are based on real perfor
To see how the performance of the tool is related to instance counts, partition counts, key distribution and how it would relate to the vanilla client.
Actual results will vary wildly depending upon the setup being deployed into.

For example, if you have hundreds of thousands of keys in your topic, randomly distributed, even with hundreds of partitions, with only a handful of this wrapper deployed, you will probably see many orders of magnitude performance improvements - massively out performing dozens of vanilla Kafka consumer clients.
For example, if you have hundreds of thousands of keys in your topic, randomly distributed, even with hundreds of partitions, with only a handful of this wrapper deployed, you will probably see many orders of magnitude performance improvements - massively outperforming dozens of vanilla Kafka consumer clients.

.Time taken to process a large number of messages with a Single Parallel Consumer vs a single Kafka Consumer, for different key space sizes. As the number of unique keys in the data set increases, the key ordered Parallel Consumer performance starts to approach that of the unordered Parallel Consumer. The raw Kafka consumer performance remains unaffected by the key distribution.
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=1691474082&format=image[align="center"]
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=1691474082&format=image[align="center"]

test1

.test1
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=1161363385&format=interactive[align="center"]

test1.5: image:https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=1161363385&format=interactive[align="center"]

test2

.test2
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=1161363385&format=image[align="center"]

test3

.test3
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=938493158&format=image[align="center"]

.Consumer group size effect on total processing time vs a single Parallel Consumer. As instances are added to the consumer group, it's performance starts to approach that of the single instance Parallel Consumer. Key ordering is faster than partition ordering, with unordered being the fastest.
image::https://docs.google.com/spreadsheets/d/e/2PACX-1vQffkAFG-_BzH-LKfGCVnytdzAHiCNIrixM6X2vF8cqw2YVz6KyW3LBXTB-lVazMAJxW0UDuFILKvtK/pubchart?oid=938493158&format=image[align="center"]
Expand Down