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alamb pushed a commit to branch alamb/better_diagrams
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commit a9882f02d99b0cf7bfd12b24c180bf5562c12d17
Author: Andrew Lamb <[email protected]>
AuthorDate: Mon Oct 17 16:53:28 2022 -0400

    Tweak markdown and add links
---
 _posts/2022-10-05-arrow-parquet-encoding-part-1.md | 6 +++---
 _posts/2022-10-08-arrow-parquet-encoding-part-2.md | 2 +-
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/_posts/2022-10-05-arrow-parquet-encoding-part-1.md 
b/_posts/2022-10-05-arrow-parquet-encoding-part-1.md
index 33d791ad92..a4688a7af8 100644
--- a/_posts/2022-10-05-arrow-parquet-encoding-part-1.md
+++ b/_posts/2022-10-05-arrow-parquet-encoding-part-1.md
@@ -44,7 +44,7 @@ First, it is necessary to take a step back and discuss the 
difference between co
 
 For example
 
-```json
+```python
 {"Column1": 1, "Column2": 2}
 {"Column1": 3, "Column2": 4, "Column3": 5}
 {"Column1": 5, "Column2": 4, "Column3": 5}
@@ -52,7 +52,7 @@ For example
 
 In a columnar representation, the data for a given column is instead stored 
contiguously
 
-```text
+```python
 Column1: [1, 3, 5]
 Column2: [2, 4, 4]
 Column3: [null, 5, 5]
@@ -147,4 +147,4 @@ Definition  Values
 
 ## Next up: Nested and Hierarchical Data
 
-Armed with the foundational understanding of how Arrow and Parquet store 
nullability / definition differently we are ready to move on to more complex 
nested types, which you can read about in our upcoming blog post on the topic 
<!-- I propose to update this text with a link when when we have published the 
next blog -->.
+Armed with the foundational understanding of how Arrow and Parquet store 
nullability / definition differently we are ready to move on to more complex 
nested types, which you can read about in our [next blog post on the 
topic](https://arrow.apache.org/blog/2022/10/08/arrow-parquet-encoding-part-2/).
diff --git a/_posts/2022-10-08-arrow-parquet-encoding-part-2.md 
b/_posts/2022-10-08-arrow-parquet-encoding-part-2.md
index 62a14925da..62bf19e6b9 100644
--- a/_posts/2022-10-08-arrow-parquet-encoding-part-2.md
+++ b/_posts/2022-10-08-arrow-parquet-encoding-part-2.md
@@ -343,6 +343,6 @@ The example above would therefore be encoded as
 
 ## Next up: Arbitrary Nesting: Lists of Structs and Structs of Lists
 
-In our final blog post <!-- When published, add link here --> we will explain 
how Parquet and Arrow combine these concepts to support arbitrary nesting of 
potentially nullable data structures.
+In our [final blog 
post](https://arrow.apache.org/blog/2022/10/17/arrow-parquet-encoding-part-3/) 
we will explain how Parquet and Arrow combine these concepts to support 
arbitrary nesting of potentially nullable data structures.
 
 If you want to store and process structured types, you will be pleased to hear 
that the Rust [parquet](https://crates.io/crates/parquet) implementation fully 
supports reading and writing directly into Arrow, as simply as any other type. 
All the complex record shredding and reconstruction is handled automatically. 
With this and other exciting features such as  [reading 
asynchronously](https://docs.rs/parquet/22.0.0/parquet/arrow/async_reader/index.html)
 from [object storage](https://docs. [...]

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