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create new images dir, update spark #185

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0 apache_spark_logo.jpeg → Images/spark-img1.jpeg
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0 spark-image1.jpg → Images/spark-img2.jpg
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0 spark-image2.jpg → Images/spark-img3.jpg
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7 changes: 3 additions & 4 deletions spark.md
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Expand Up @@ -103,8 +103,7 @@ As mentioned above and on other CARC web pages, we suggest that users use Anacon
```wheeler-sn> module load anaconda3-4.4.0-gcc-4.8.5-ubgzkkv
wheeler-sn> conda create –n spark python=27 numpy scipy pandas matplotlib
```
![SparkLogo](https://github.com/UNM-CARC/QuickBytes/blob/master/apache_spark_logo.jpeg)

![](/Images/spark-img1.jpeg)
Once this is done, we just activate that environment and can add new things to it as needed after we launch our Spark cluster, to interactively look at a lot of data. First, we bring up Spark with this customized environment:

```wheeler-sn> qsub –I –l nodes=1:ppn=8 -l walltime=01:00:00
Expand Down Expand Up @@ -172,7 +171,7 @@ plt.xticks(size = 18)
plt.yticks(size = 18)
plt.savefig("crimes-by-month.pdf")
```
![Crimes](https://github.com/UNM-CARC/QuickBytes/blob/master/spark-image1.jpg)
![](/Images/spark-img2.jpg)

Similarly, this code generates a file which charts Chicago crime by location type:

Expand All @@ -192,7 +191,7 @@ plt.xticks(size = 24)
plt.yticks(size = 24)
plt.savefig("crimes-by-location.pdf")
```
![Crimes](https://github.com/UNM-CARC/QuickBytes/blob/master/spark-image2.jpg)
![](/Images/spark-img3.jpg)


## More Information
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