[arrow-site] branch master updated: Minor tweaks to querying parquet with millisecond latency (#307)

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tustvold pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/arrow-site.git


The following commit(s) were added to refs/heads/master by this push:
     new 2a56e169687 Minor tweaks to querying parquet with millisecond latency (#307)
2a56e169687 is described below

commit 2a56e169687d66db79818f0cf017b7aa08af2954
Author: Raphael Taylor-Davies <17...@users.noreply.github.com>
AuthorDate: Mon Jan 30 14:12:05 2023 +0000

    Minor tweaks to querying parquet with millisecond latency (#307)
    
    Just some minor things I noticed whilst reading the blog again
---
 _posts/2022-12-26-querying-parquet-with-millisecond-latency.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/_posts/2022-12-26-querying-parquet-with-millisecond-latency.md b/_posts/2022-12-26-querying-parquet-with-millisecond-latency.md
index e5919b64e34..4a4a91d02af 100644
--- a/_posts/2022-12-26-querying-parquet-with-millisecond-latency.md
+++ b/_posts/2022-12-26-querying-parquet-with-millisecond-latency.md
@@ -29,7 +29,7 @@ limitations under the License.
 
 We believe that querying data in [Apache Parquet](https://parquet.apache.org/) files directly can achieve similar or better storage efficiency and query performance than most specialized file formats. While it requires significant engineering effort, the benefits of Parquet's open format and broad ecosystem support make it the obvious choice for a wide class of data systems.
 
-In this article we explain several advanced techniques needed to query data stored in the Parquet format quickly that we implemented in the [Apache Arrow Rust Parquet reader](https://docs.rs/parquet/27.0.0/parquet/). Together these techniques make the Rust implementation one of, if not the, fastest implementation for querying Parquet files — be it on local disk or remote object storage. It is able to query GBs of Parquet in a [matter of milliseconds](https://github.com/tustvold/access-lo [...]
+In this article we explain several advanced techniques needed to query data stored in the Parquet format quickly that we implemented in the [Apache Arrow Rust Parquet reader](https://docs.rs/parquet/27.0.0/parquet/). Together these techniques make the Rust implementation one of, if not the fastest implementation for querying Parquet files — be it on local disk or remote object storage. It is able to query GBs of Parquet in a [matter of milliseconds](https://github.com/tustvold/access-log [...]
 
 We would like to acknowledge and thank [InfluxData](https://www.influxdata.com/) for their support of this work. InfluxData has a deep and continuing commitment to Open source software, and it sponsored much of our time for writing this blog post as well as many contributions as part of building the [InfluxDB IOx Storage Engine](https://www.influxdata.com/blog/influxdb-engine/).
 
@@ -493,8 +493,8 @@ While Parquet was designed for efficient access on the [HDFS distributed file sy
 
 
 * **Relatively slow “random access” reads**: it is much more efficient to read large (MBs) sections of data in each request than issue many requests for smaller portions
-* **Significant latency before retrieving the first byte **
-* **High per-request cost: **Often billed per request, regardless of number of bytes read, which incentivizes fewer requests that each read a large contiguous section of data.
+* **Significant latency before retrieving the first byte**
+* **High per-request cost:** Often billed per request, regardless of number of bytes read, which incentivizes fewer requests that each read a large contiguous section of data.
 
 To read optimally from such systems, a Parquet reader must: